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+ "requires_cloud": false, + "requires_wsl": false, + "executable_locally": true + }, + { + "path": "GameTheory/GameTheory-07-ExtensiveForm-CSharp.ipynb", + "title": "GameTheory-07-ExtensiveForm-Python (Twin C#)", "serie": "GameTheory", "sous_serie": "", "kernel": ".NET (C#)", @@ -3332,8 +3456,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "0bbbfb40f", - "executed_at": "2026-08-23T14:10:30+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -3351,14 +3475,14 @@ "history": "COMPLETE", "revisions": 1, "authors": 1, - "first_commit": "2026-08-23", + "first_commit": "2026-09-30", "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-23", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#11840, #12241", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 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"issue_pr_associee": "#11840, #12241", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 35, "cells_code": 15, "cells_markdown": 20, @@ -3432,8 +3556,8 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-08-CombinatorialGames-Csharp.ipynb", - "title": "GameTheory-08-CombinatorialGames (C#)", + "path": "GameTheory/GameTheory-08-CombinatorialGames-CSharp.ipynb", + "title": "GameTheory 8 - Jeux Combinatoires (Twin C#)", "serie": "GameTheory", "sous_serie": "", "kernel": ".NET (C#)", @@ -3454,8 +3578,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "dad388913", - "executed_at": "2026-09-26T12:26:24+02:00", + "last_success_sha": "78cd444f0", + "executed_at": "2026-10-02T08:13:56+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -3469,18 +3593,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 4, + "revisions": 2, "authors": 1, - "first_commit": "2026-08-23", - "span_days": 34 + "first_commit": "2026-09-30", + "span_days": 2 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-26", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17040, #17062", + "issue_pr_associee": "#17107, #18711", "cells_total": 32, "cells_code": 11, "cells_markdown": 21, @@ -3493,7 +3617,7 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-08-CombinatorialGames.ipynb", + "path": "GameTheory/GameTheory-08-CombinatorialGames-Python.ipynb", "title": "GameTheory 8 - Jeux Combinatoires", "serie": "GameTheory", "sous_serie": "", @@ -3515,8 +3639,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "d7ddfc2ae", - "executed_at": "2026-09-21T23:02:38+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -3530,18 +3654,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 3, + "revisions": 1, "authors": 1, - "first_commit": "2026-08-23", - "span_days": 29 + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-21", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#13410, #16471", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 34, "cells_code": 11, "cells_markdown": 23, @@ -3554,7 +3678,7 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-08b-Lean-CombinatorialGames.ipynb", + "path": "GameTheory/GameTheory-08b-Lean-CombinatorialGames-Lean.ipynb", "title": "GameTheory 8b - Jeux Combinatoires en Lean", "serie": "GameTheory", "sous_serie": "", @@ -3576,8 +3700,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "8958e6579", - "executed_at": "2026-09-05T12:12:58+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "15min", "resource_cost": { @@ -3593,18 +3717,18 @@ ] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 3, + "revisions": 1, "authors": 1, - "first_commit": "2026-08-23", - "span_days": 13 + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-05", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14209, #14723", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 22, "cells_code": 7, "cells_markdown": 15, @@ -3617,7 +3741,7 @@ "executable_locally": false }, { - "path": "GameTheory/GameTheory-08c-CombinatorialGames-Csharp.ipynb", + "path": "GameTheory/GameTheory-08c-CombinatorialGames-CSharp.ipynb", "title": "GameTheory 8c - Jeux Combinatoires : Approfondissement --- twin C# .NET", "serie": "GameTheory", "sous_serie": "", @@ -3639,8 +3763,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "0bbbfb40f", - "executed_at": "2026-08-23T14:10:30+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -3658,14 +3782,14 @@ "history": "COMPLETE", "revisions": 1, "authors": 1, - "first_commit": "2026-08-23", + "first_commit": "2026-09-30", "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-23", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#11840, #12241", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 31, "cells_code": 14, "cells_markdown": 17, @@ -3700,8 +3824,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "dad388913", - "executed_at": "2026-09-26T12:26:24+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -3717,16 +3841,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 5, + "revisions": 6, "authors": 1, "first_commit": "2026-08-23", - "span_days": 34 + "span_days": 38 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-26", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17040, #17062", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 40, "cells_code": 14, "cells_markdown": 26, @@ -3739,7 +3863,7 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-08d-Lean-CGT-Native.ipynb", + "path": "GameTheory/GameTheory-08d-Lean-CGT-Lean.ipynb", "title": "GameTheory 8d - Combinatorial Games natif : le lake conway_cgt_lean", "serie": "GameTheory", "sous_serie": "", @@ -3761,8 +3885,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "254fff9a6", - "executed_at": "2026-09-21T14:34:27+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -3778,18 +3902,18 @@ ] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 4, - "authors": 2, - "first_commit": "2026-08-23", - "span_days": 29 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-21", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#13410, #16395", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 23, "cells_code": 10, "cells_markdown": 13, @@ -3802,8 +3926,8 @@ "executable_locally": false }, { - "path": "GameTheory/GameTheory-09-BackwardInduction-Csharp.ipynb", - "title": "GameTheory-09-BackwardInduction (C#)", + "path": "GameTheory/GameTheory-09-BackwardInduction-CSharp.ipynb", + "title": "GameTheory-09-BackwardInduction-Python (C#)", "serie": "GameTheory", "sous_serie": "", "kernel": ".NET (C#)", @@ -3824,8 +3948,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "0bbbfb40f", - "executed_at": "2026-08-23T14:10:30+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -3843,14 +3967,14 @@ "history": "COMPLETE", "revisions": 1, "authors": 1, - "first_commit": "2026-08-23", + "first_commit": "2026-09-30", "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-23", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#11840, #12241", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 26, "cells_code": 11, "cells_markdown": 15, @@ -3863,8 +3987,8 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-09-BackwardInduction.ipynb", - "title": "GameTheory-09-BackwardInduction", + "path": "GameTheory/GameTheory-09-BackwardInduction-Python.ipynb", + "title": "GameTheory-09-BackwardInduction-Python", "serie": "GameTheory", "sous_serie": "", "kernel": "Python 3", @@ -3885,8 +4009,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "fb77b7e52", - "executed_at": "2026-09-22T23:32:42+02:00", + "last_success_sha": "25ac2750d", + "executed_at": "2026-09-30T16:04:27+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -3900,18 +4024,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 3, - "authors": 2, - "first_commit": "2026-08-23", - "span_days": 30 + "revisions": 2, + "authors": 1, + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-22", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#13410, #16467", + "issue_pr_associee": "#17636, #18539", "cells_total": 39, "cells_code": 15, "cells_markdown": 24, @@ -3924,7 +4048,7 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-09b-Commitment-Stackelberg.ipynb", + "path": "GameTheory/GameTheory-09b-Commitment-Stackelberg-Python.ipynb", "title": "Stackelberg : la performativité sans mystère", "serie": "GameTheory", "sous_serie": "", @@ -3946,8 +4070,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "18bf7c73a", - "executed_at": "2026-09-25T06:22:27+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -3961,18 +4085,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 3, - "authors": 2, - "first_commit": "2026-08-30", - "span_days": 26 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-25", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17107, #17690", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 25, "cells_code": 11, "cells_markdown": 14, @@ -3985,7 +4109,7 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-09c-Stackelberg-SecurityGame.ipynb", + "path": "GameTheory/GameTheory-09c-Stackelberg-SecurityGame-Python.ipynb", "title": "GameTheory-09c : Stackelberg Security Game — patrouille, capteur imparfait, signaling", "serie": "GameTheory", "sous_serie": "", @@ -4007,8 +4131,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "15min", "resource_cost": { @@ -4024,16 +4148,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 2, - "authors": 2, - "first_commit": "2026-08-30", - "span_days": 1 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", + "last_validation": "2026-09-30", + "last_validator": "jsboige@gmail.com", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 14, "cells_code": 7, "cells_markdown": 7, @@ -4046,7 +4170,7 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-10-ForwardInduction-SPE-Csharp.ipynb", + "path": "GameTheory/GameTheory-10-ForwardInduction-SPE-CSharp.ipynb", "title": "GameTheory-10 — Équilibres Parfaits de Sous-Jeux et Induction Avant (Twin C#)", "serie": "GameTheory", "sous_serie": "", @@ -4068,8 +4192,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "dad388913", - "executed_at": "2026-09-26T12:26:24+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4083,18 +4207,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 10, - "authors": 2, - "first_commit": "2026-07-07", - "span_days": 81 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-26", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17040, #17062", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 40, "cells_code": 14, "cells_markdown": 26, @@ -4107,8 +4231,8 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-10-ForwardInduction-SPE.ipynb", - "title": "GameTheory-10-ForwardInduction-SPE", + "path": "GameTheory/GameTheory-10-ForwardInduction-SPE-Python.ipynb", + "title": "GameTheory-10-ForwardInduction-SPE-Python", "serie": "GameTheory", "sous_serie": "", "kernel": "Python 3", @@ -4129,8 +4253,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "e1843e885", - "executed_at": "2026-09-12T03:34:11+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4144,18 +4268,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 31, - "authors": 2, - "first_commit": "2026-01-31", - "span_days": 224 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-12", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#15429, #15446", + "last_validation": "2026-09-30", + "last_validator": "jsboige@gmail.com", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 37, "cells_code": 15, "cells_markdown": 22, @@ -4168,8 +4292,8 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-11-BayesianGames-Csharp.ipynb", - "title": "GameTheory-11-BayesianGames-Csharp", + "path": "GameTheory/GameTheory-11-BayesianGames-CSharp.ipynb", + "title": "GameTheory-11-BayesianGames-CSharp", "serie": "GameTheory", "sous_serie": "", "kernel": ".NET (C#)", @@ -4190,8 +4314,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "ed45c1cee", - "executed_at": "2026-09-01T04:46:22+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4205,18 +4329,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 8, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-06", - "span_days": 57 + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-01", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#13410, #13919", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 34, "cells_code": 13, "cells_markdown": 21, @@ -4229,8 +4353,8 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-11-BayesianGames.ipynb", - "title": "GameTheory-11-BayesianGames", + "path": "GameTheory/GameTheory-11-BayesianGames-Python.ipynb", + "title": "GameTheory-11-BayesianGames-Python", "serie": "GameTheory", "sous_serie": "", "kernel": "Python 3", @@ -4251,8 +4375,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4266,18 +4390,18 @@ "external": [] }, "creation": { - "class": "VERY_HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 42, - "authors": 3, - "first_commit": "2026-01-31", - "span_days": 212 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", + "last_validation": "2026-09-30", + "last_validator": "jsboige@gmail.com", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 48, "cells_code": 15, "cells_markdown": 33, @@ -4290,7 +4414,7 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-11b-Lean-BayesianGamesExt.ipynb", + "path": "GameTheory/GameTheory-11b-Lean-BayesianGamesExt-Lean.ipynb", "title": "GameTheory-11b — Jeux Bayésiens en Lean 4 (companion)", "serie": "GameTheory", "sous_serie": "", @@ -4312,8 +4436,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "d0dc82b73", - "executed_at": "2026-09-03T22:02:01+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4329,18 +4453,18 @@ ] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 6, - "authors": 2, - "first_commit": "2026-06-25", - "span_days": 70 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-03", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14174, #14174", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 43, "cells_code": 19, "cells_markdown": 24, @@ -4353,7 +4477,7 @@ "executable_locally": false }, { - "path": "GameTheory/GameTheory-12-ReputationGames-Csharp.ipynb", + 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+4636,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 9, - "authors": 2, - "first_commit": "2026-07-06", - "span_days": 77 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-21", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#13410, #16469", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 30, "cells_code": 11, "cells_markdown": 19, @@ -4536,7 +4660,7 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-13-ImperfectInfo-CFR.ipynb", + "path": "GameTheory/GameTheory-13-ImperfectInfo-CFR-Python.ipynb", "title": "GameTheory-13 : Jeux a Information Imparfaite et CFR", "serie": "GameTheory", "sous_serie": "", @@ -4558,8 +4682,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "85e974425", - "executed_at": "2026-09-14T02:03:01+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "1h", "resource_cost": { @@ -4575,18 +4699,18 @@ ] }, "creation": { - "class": "VERY_HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 36, - "authors": 3, - "first_commit": "2026-01-31", - "span_days": 226 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-14", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#12797, #15961", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 66, "cells_code": 26, "cells_markdown": 40, @@ -4599,7 +4723,7 @@ "executable_locally": false }, { - "path": "GameTheory/GameTheory-13b-Safe-Subgame-Solving.ipynb", + "path": "GameTheory/GameTheory-13b-Safe-Subgame-Solving-Python.ipynb", "title": "GameTheory-13b : Safe Subgame Solving -- quand le mauvais recollement produit un temoin adversarial", "serie": "GameTheory", "sous_serie": "", @@ -4621,8 +4745,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "8958e6579", - "executed_at": "2026-09-05T12:12:58+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -4636,18 +4760,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 7, + "revisions": 1, "authors": 1, - "first_commit": "2026-08-23", - "span_days": 13 + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-05", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14209, #14723", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 26, "cells_code": 12, "cells_markdown": 14, @@ 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"jsboige@gmail.com", - "issue_pr_associee": "#11601, #16295", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 24, "cells_code": 10, "cells_markdown": 14, @@ -4721,7 +4845,7 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-13d-Optimistic-CFR.ipynb", + "path": "GameTheory/GameTheory-13d-Optimistic-CFR-Python.ipynb", "title": "GameTheory-13d : Optimistic Counterfactual Regret Minimization (OFTRL stable-prédictif)", "serie": "GameTheory", "sous_serie": "", @@ -4736,40 +4860,40 @@ "scientific_review_detail": { "grade": "UNASSESSED", "stale": false, - "code_sha": "69a583fb12dfe1e43a5e244d6fae21bbbaf4022e2f2c77678013d9c025f85b56", + "code_sha": "f863827f7bb38b576ac6c0b56185c68c3f9ed13e014c58f6561156dfb64f18d6", "reviewed_code_sha": "", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - "last_success_sha": "e8e4642d8", - "executed_at": "2026-09-27T01:38:13+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": 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"GameTheory-14 : Jeux Differentiels et Equilibres de Stackelberg (C#)", "serie": "GameTheory", "sous_serie": "", @@ -4804,8 +4928,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4819,18 +4943,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 8, - "authors": 2, - "first_commit": "2026-07-07", - "span_days": 55 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", + "last_validation": "2026-09-30", + "last_validator": "jsboige@gmail.com", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 29, "cells_code": 12, "cells_markdown": 17, @@ -4843,7 +4967,7 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-14-DifferentialGames.ipynb", + "path": "GameTheory/GameTheory-14-DifferentialGames-Python.ipynb", "title": "GameTheory-14 : Jeux Differentiels et Equilibres de Stackelberg", "serie": "GameTheory", "sous_serie": "", @@ -4865,8 +4989,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "18ac7dbca", - "executed_at": "2026-09-23T00:06:34+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4880,18 +5004,18 @@ "external": [] }, "creation": { - "class": "VERY_HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 37, - "authors": 3, - "first_commit": "2026-01-31", - "span_days": 235 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-23", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16472, #16612", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 51, "cells_code": 19, "cells_markdown": 32, @@ -4904,7 +5028,7 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-15-CooperativeGames-Csharp.ipynb", + "path": "GameTheory/GameTheory-15-CooperativeGames-CSharp.ipynb", "title": "GameTheory-15 — Jeux Coopératifs (Twin C#)", "serie": "GameTheory", "sous_serie": "", @@ -4926,8 +5050,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "0bbbfb40f", - "executed_at": "2026-08-23T14:10:30+02:00", + "last_success_sha": "09e96fa5e", + "executed_at": "2026-09-30T00:39:31+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "1h", "resource_cost": { @@ -4941,18 +5065,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 7, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-07", - "span_days": 47 + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-23", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#11840, #12241", + "issue_pr_associee": "#16231, #14944, #18001", "cells_total": 64, "cells_code": 24, "cells_markdown": 40, @@ -4965,8 +5089,8 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-15-CooperativeGames.ipynb", - "title": "GameTheory-15-CooperativeGames", + "path": "GameTheory/GameTheory-15-CooperativeGames-Python.ipynb", + "title": "GameTheory-15-CooperativeGames-Python", "serie": "GameTheory", "sous_serie": "", "kernel": "Python 3 (ipykernel)", @@ -4987,8 +5111,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "f83278a0d", - "executed_at": "2026-09-26T18:55:18+02:00", + "last_success_sha": "db631820f", + "executed_at": "2026-09-30T20:05:30+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "1h", "resource_cost": { @@ -5002,18 +5126,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 33, + "revisions": 2, "authors": 1, - "first_commit": "2026-01-31", - "span_days": 238 + "first_commit": "2026-09-30", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-26", + "last_validation": "2026-09-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17498, #17754", + "issue_pr_associee": "#17529, #18498", "cells_total": 68, "cells_code": 30, "cells_markdown": 38, @@ -5026,7 +5150,7 @@ "executable_locally": true }, { - "path": "GameTheory/GameTheory-15b-Lean-CooperativeGames.ipynb", + "path": "GameTheory/GameTheory-15b-Lean-CooperativeGames-Lean.ipynb", "title": "GameTheory 15b - Jeux Cooperatifs en Lean : Formalisation de Shapley", "serie": "GameTheory", "sous_serie": "", @@ -5048,8 +5172,8 @@ 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"issue_pr_associee": "#16472, #16528", + "issue_pr_associee": "#18512, #18529", "cells_total": 28, "cells_code": 14, "cells_markdown": 14, @@ -23485,26 +24174,26 @@ "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "RESEARCH", - "scientific_review_stale": false, + "scientific_review_stale": true, "scientific_review_detail": { "grade": "RESEARCH", - "stale": false, - "code_sha": "e0ee9503aec8cf28f65ba4425eac82e50f7bf541405b88ebf313620f4361a8d0", + "stale": true, + "code_sha": "99b6cd8071298c15792559d4e0352a6d0682e3115ec783b6edd8697f422598fc", "reviewed_code_sha": "e0ee9503aec8cf28f65ba4425eac82e50f7bf541405b88ebf313620f4361a8d0", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - "last_success_sha": "f6f49dd80", - "executed_at": "2026-09-26T11:36:49+02:00", + "last_success_sha": "f6b8b2864", + "executed_at": "2026-09-28T03:37:00+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { "schema": 1, "execution": { "class": "LIGHT", - 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"last_success_sha": "a104c40c4", - "executed_at": "2026-09-18T22:43:01+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -23755,18 +24444,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 5, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-02", - "span_days": 78 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16696", + "issue_pr_associee": "#16231, #18649", "cells_total": 27, "cells_code": 11, "cells_markdown": 16, @@ -23779,7 +24468,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-12-ValenceFieldsAndAnimats.ipynb", + "path": "IIT/ICT-Series/ICT-12-ValenceFieldsAndAnimats-Python.ipynb", "title": "ICT-12 — Champs de valence et animats : rôles mesures, modèle interne payant ou ruineux", "serie": "IIT", "sous_serie": "ICT-Series", @@ -23801,8 +24490,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "a104c40c4", - "executed_at": "2026-09-18T22:43:01+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -23816,18 +24505,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 7, - "authors": 2, - "first_commit": "2026-07-02", - "span_days": 78 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16696", + "issue_pr_associee": "#16231, #18649", "cells_total": 29, "cells_code": 11, "cells_markdown": 18, @@ -23840,7 +24529,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-12b-LearnedValence.ipynb", + "path": "IIT/ICT-Series/ICT-12b-LearnedValence-Python.ipynb", "title": "ICT-12b — Valence APPRISE, transferable, reversible : l'expérience manquante (#7740)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -23862,8 +24551,8 @@ "sorry_free": false }, "production_signed": false, - 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"last_success_sha": "a104c40c4", - "executed_at": "2026-09-18T22:43:01+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -23938,18 +24627,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 5, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-30", - "span_days": 50 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16696", + "issue_pr_associee": "#16231, #18649", "cells_total": 36, "cells_code": 12, "cells_markdown": 24, @@ -23962,7 +24651,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-12d-InhibitedActionAnimat.ipynb", + "path": "IIT/ICT-Series/ICT-12d-InhibitedActionAnimat-Python.ipynb", "title": "ICT-12d — Animat inhibé (Laborit) : contrôlabilité, rigidification, dette d'irréversibilité (#7741)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -23984,8 +24673,8 @@ "sorry_free": false }, "production_signed": false, - 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"last_success_sha": "9bccdb6ee", - "executed_at": "2026-09-21T11:05:46+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -24060,18 +24749,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 4, + "revisions": 1, "authors": 1, - "first_commit": "2026-08-31", - "span_days": 21 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-21", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17026", + "issue_pr_associee": "#16231, #18649", "cells_total": 23, "cells_code": 8, "cells_markdown": 15, @@ -24084,7 +24773,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-13-AxelrodStrategicMorphodynamics.ipynb", + "path": "IIT/ICT-Series/ICT-13-AxelrodStrategicMorphodynamics-Python.ipynb", "title": "ICT-13 — Morphodynamique stratégique : une stratégie est-elle une forme stable ?", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24106,8 +24795,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "1afad0cd0", - "executed_at": "2026-09-25T18:36:32+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -24121,18 +24810,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 14, - "authors": 2, - "first_commit": "2026-07-02", - "span_days": 85 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-25", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17040, #17047", + "issue_pr_associee": "#16231, #18649", "cells_total": 46, "cells_code": 21, "cells_markdown": 25, @@ -24145,7 +24834,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-13b-DecroisementDynamiqueObservable.ipynb", + "path": "IIT/ICT-Series/ICT-13b-DecroisementDynamiqueObservable-Python.ipynb", "title": "ICT-13b — Décroisement dynamique × observable : d'où vient le relief du substrat Axelrod", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24167,8 +24856,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "9bccdb6ee", - "executed_at": "2026-09-21T11:05:46+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -24182,18 +24871,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 4, - "authors": 2, - "first_commit": "2026-08-29", - "span_days": 23 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-21", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17026", + "issue_pr_associee": "#16231, #18649", "cells_total": 32, "cells_code": 11, "cells_markdown": 21, @@ -24206,7 +24895,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-14-FreeEnergySurprise.ipynb", + "path": "IIT/ICT-Series/ICT-14-FreeEnergySurprise-Python.ipynb", "title": "ICT-14 — Énergie libre et surprise du représentant interne", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24228,8 +24917,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "dfdecbe67", - "executed_at": "2026-09-18T22:51:57+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -24243,18 +24932,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 5, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-03", - "span_days": 77 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16698", + "issue_pr_associee": "#16231, #18649", "cells_total": 22, "cells_code": 8, "cells_markdown": 14, @@ -24267,7 +24956,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-14b-ActiveInferenceEFE.ipynb", + "path": "IIT/ICT-Series/ICT-14b-ActiveInferenceEFE-Python.ipynb", "title": "ICT-14b — Inférence active : l'expected free energy pilote l'action", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24289,8 +24978,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "012032c43", - "executed_at": "2026-09-22T23:10:20+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -24304,18 +24993,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 4, + "revisions": 1, "authors": 1, - "first_commit": "2026-08-06", - "span_days": 47 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-22", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17024", + "issue_pr_associee": "#16231, #18649", "cells_total": 25, "cells_code": 10, "cells_markdown": 15, @@ -24328,7 +25017,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-15-IntegratedComplexity.ipynb", + "path": "IIT/ICT-Series/ICT-15-IntegratedComplexity-Python.ipynb", "title": "ICT-15 — Integrated Complexity : convergence Φ / F / K (capstone strate 4)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24350,8 +25039,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "dfdecbe67", - "executed_at": "2026-09-18T22:51:57+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -24365,18 +25054,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 7, - "authors": 2, - "first_commit": "2026-07-03", - "span_days": 77 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16698", + "issue_pr_associee": "#16231, #18649", "cells_total": 25, "cells_code": 8, "cells_markdown": 17, @@ -24389,7 +25078,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-15b-SensitivityCanonicity.ipynb", + "path": "IIT/ICT-Series/ICT-15b-SensitivityCanonicity-Python.ipynb", "title": "ICT-15b -- Sensitivity Canonicity (Huang 2019 transpose au zoo ICT)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24411,8 +25100,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "dfdecbe67", - "executed_at": "2026-09-18T22:51:57+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -24426,18 +25115,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 10, - "authors": 2, - "first_commit": "2026-07-20", - "span_days": 60 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16698", + "issue_pr_associee": "#16231, #18649", "cells_total": 43, "cells_code": 17, "cells_markdown": 26, @@ -24450,7 +25139,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-15c-MetaProxyObstruction.ipynb", + "path": "IIT/ICT-Series/ICT-15c-MetaProxyObstruction-Python.ipynb", "title": "ICT-15c — Méta-proxy d'obstruction : structure des désaccords entre proxys", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24472,8 +25161,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "dfdecbe67", - "executed_at": "2026-09-18T22:51:57+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -24487,18 +25176,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 9, - "authors": 3, - "first_commit": "2026-07-20", - "span_days": 60 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16698", + "issue_pr_associee": "#16231, #18649", "cells_total": 23, "cells_code": 11, "cells_markdown": 12, @@ -24511,7 +25200,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-15d-CechObstruction.ipynb", + "path": "IIT/ICT-Series/ICT-15d-CechObstruction-Python.ipynb", "title": "ICT-15d — Cochaîne de Čech pondérée : obstruction intra-substrat", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24533,8 +25222,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "dfdecbe67", - "executed_at": "2026-09-18T22:51:57+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -24548,18 +25237,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 6, - "authors": 3, - "first_commit": "2026-08-04", - "span_days": 45 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16698", + "issue_pr_associee": "#16231, #18649", "cells_total": 22, "cells_code": 9, "cells_markdown": 13, @@ -24572,7 +25261,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-15e-Bridge2-RecoverabilityAgency.ipynb", + "path": "IIT/ICT-Series/ICT-15e-Bridge2-RecoverabilityAgency-Python.ipynb", "title": "ICT-15e -- Bridge #2 : recouvrabilite *est* agentivite (≠ simple gain de reparation)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24587,40 +25276,40 @@ "scientific_review_detail": { "grade": "RESEARCH", "stale": true, - "code_sha": "997153fb58b06c05665701b1e7889ecb889d02f0e78afb181c2a06f298ae6eb1", + "code_sha": "8855c8c4111f233e7f139cb4c7a9f9b33e89b5e646f69239745363c05feb5bd8", "reviewed_code_sha": "3a9b70a316b2ab08ef6dd9fece703e97df070eb74005b37dff078654cc7b2ee0", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - "last_success_sha": "487efb059", - "executed_at": "2026-09-21T21:06:33+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { "schema": 1, "execution": { "class": "LIGHT", - "wall_seconds": 9.8, + "wall_seconds": 15.4, "cells_timed": 10, "cells_code": 10, "coverage": "FULL", "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 6, + "revisions": 1, "authors": 1, - "first_commit": "2026-08-05", - "span_days": 47 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-21", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#2161, #16441", + "issue_pr_associee": "#16231, #18649", "cells_total": 25, "cells_code": 10, "cells_markdown": 15, @@ -24633,7 +25322,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-15f-Bridge1bis-DecoupledFamily.ipynb", + "path": "IIT/ICT-Series/ICT-15f-Bridge1bis-DecoupledFamily-Python.ipynb", "title": "ICT-15f -- Pont #1-bis : la famille decouplee tranche le negatif de sigma", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24655,8 +25344,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "9bccdb6ee", - "executed_at": "2026-09-21T11:05:46+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -24670,18 +25359,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 3, + "revisions": 1, "authors": 1, - "first_commit": "2026-08-06", - "span_days": 46 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-21", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17026", + "issue_pr_associee": "#16231, #18649", "cells_total": 24, "cells_code": 8, "cells_markdown": 16, @@ -24694,7 +25383,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-15g-EmpiricalHuangExploitation.ipynb", + "path": "IIT/ICT-Series/ICT-15g-EmpiricalHuangExploitation-Python.ipynb", "title": "ICT-15g -- Exploitation empirique de la sensibilite (Huang 2019) sur substrats reels ICT-15c", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24705,48 +25394,48 @@ "editorial": "DRAFT", "reproducibility": "EXECUTED", "scientific_review": "RESEARCH", - "scientific_review_stale": false, + "scientific_review_stale": true, "scientific_review_detail": { "grade": "RESEARCH", - "stale": false, - "code_sha": "7d4b66eda31f97fa86c0ea89e3e22c4d23d5bb9bd2b6cdbe9cbdba7510e8235a", + "stale": true, + "code_sha": "ff88ddfccd003ebec348a74adde2b1059f0b1e4542b53b9f22355ebf54d587d1", "reviewed_code_sha": "7d4b66eda31f97fa86c0ea89e3e22c4d23d5bb9bd2b6cdbe9cbdba7510e8235a", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - "last_success_sha": "9bccdb6ee", - "executed_at": "2026-09-21T11:05:46+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { "schema": 1, "execution": { "class": "LIGHT", - "wall_seconds": 0.8, - "cells_timed": 10, - "cells_code": 10, + "wall_seconds": 5.5, + "cells_timed": 13, + "cells_code": 13, "coverage": "FULL", "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 4, - "authors": 2, - "first_commit": "2026-08-07", - "span_days": 45 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-21", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17026", - "cells_total": 17, - "cells_code": 10, - "cells_markdown": 7, - "cells_with_outputs": 9, + "issue_pr_associee": "#16231, #18649", + "cells_total": 21, + "cells_code": 13, + "cells_markdown": 8, + "cells_with_outputs": 12, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -24755,7 +25444,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-15h-Bridge1bis-AsymmetricFamily.ipynb", + "path": "IIT/ICT-Series/ICT-15h-Bridge1bis-AsymmetricFamily-Python.ipynb", "title": "ICT-15h -- Pont #1-bis (chantier 2/3) : le regime asymetrique confirme le negatif de $\\sigma$", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24777,8 +25466,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "9bccdb6ee", - "executed_at": "2026-09-21T11:05:46+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -24792,18 +25481,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 6, - "authors": 2, - "first_commit": "2026-08-07", - "span_days": 45 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-21", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17026", + "issue_pr_associee": "#16231, #18649", "cells_total": 28, "cells_code": 9, "cells_markdown": 19, @@ -24816,7 +25505,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-15i-Bridge1bis-2DLandscape.ipynb", + "path": "IIT/ICT-Series/ICT-15i-Bridge1bis-2DLandscape-Python.ipynb", "title": "ICT-15i -- Pont #1-bis : le paysage 2D anisotrope clot l'Epic", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24838,8 +25527,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "9bccdb6ee", - "executed_at": "2026-09-21T11:05:46+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -24853,18 +25542,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 5, + "revisions": 1, "authors": 1, - "first_commit": "2026-08-07", - "span_days": 45 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-21", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17026", + "issue_pr_associee": "#16231, #18649", "cells_total": 27, "cells_code": 9, "cells_markdown": 18, @@ -24877,7 +25566,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-15j-NerveDiscriminant.ipynb", + "path": "IIT/ICT-Series/ICT-15j-NerveDiscriminant-Python.ipynb", "title": "ICT-15j — Discriminant Čech par nerf simplicial (gudhi)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24899,8 +25588,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "9bccdb6ee", - "executed_at": "2026-09-21T11:05:46+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -24914,18 +25603,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 6, - "authors": 2, - "first_commit": "2026-08-24", - "span_days": 28 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-21", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17026", + "issue_pr_associee": "#16231, #18649", "cells_total": 21, "cells_code": 9, "cells_markdown": 12, @@ -24938,7 +25627,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-15k-RecollementMacroCells.ipynb", + "path": "IIT/ICT-Series/ICT-15k-RecollementMacroCells-Python.ipynb", "title": "ICT-15k — Recollement des macrocells : le quadtree de Hashlife comme espace etale", "serie": "IIT", "sous_serie": "ICT-Series", @@ -24960,8 +25649,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "9bccdb6ee", - "executed_at": "2026-09-21T11:05:46+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -24975,18 +25664,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 4, + "revisions": 1, "authors": 1, - "first_commit": "2026-08-23", - "span_days": 29 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-21", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17026", + "issue_pr_associee": "#16231, #18649", "cells_total": 36, "cells_code": 12, "cells_markdown": 24, @@ -24999,7 +25688,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-15l-IndependanceGenerateur.ipynb", + "path": "IIT/ICT-Series/ICT-15l-IndependanceGenerateur-Python.ipynb", "title": "ICT-15l — Indépendance au générateur de nouveauté : le relief b1 survit-il au contrôle de dimension ?", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25021,8 +25710,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "9bccdb6ee", - "executed_at": "2026-09-21T11:05:46+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -25036,18 +25725,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 3, + "revisions": 1, "authors": 1, - "first_commit": "2026-08-29", - "span_days": 23 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-21", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17026", + "issue_pr_associee": "#16231, #18649", "cells_total": 23, "cells_code": 10, "cells_markdown": 13, @@ -25060,7 +25749,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-16-MDLTwoPartCode.ipynb", + "path": "IIT/ICT-Series/ICT-16-MDLTwoPartCode-Python.ipynb", "title": "ICT-16 — MDL / code en deux parties et bosse complexite-entropie", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25082,8 +25771,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "9882979fc", - "executed_at": "2026-09-25T22:19:02+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -25097,18 +25786,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 8, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-03", - "span_days": 84 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-25", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17498, #17755", + "issue_pr_associee": "#16231, #18649", "cells_total": 29, "cells_code": 12, "cells_markdown": 17, @@ -25121,7 +25810,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-17-EpsilonMachine.ipynb", + "path": "IIT/ICT-Series/ICT-17-EpsilonMachine-Python.ipynb", "title": "ICT-17 -- Mecanique computationnelle (epsilon-machine de Crutchfield)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25143,8 +25832,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "dfdecbe67", - "executed_at": "2026-09-18T22:51:57+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -25158,18 +25847,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 9, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-03", - "span_days": 77 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16698", + "issue_pr_associee": "#16231, #18649", "cells_total": 28, "cells_code": 11, "cells_markdown": 17, @@ -25182,7 +25871,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-17b-Grokking-CompressionProgress.ipynb", + "path": "IIT/ICT-Series/ICT-17b-Grokking-CompressionProgress-Python.ipynb", "title": "ICT-17b — Grokking et compression-progress : la jambe K à l'épreuve de l'entraînement", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25193,48 +25882,48 @@ "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "RESEARCH", - "scientific_review_stale": false, + "scientific_review_stale": true, "scientific_review_detail": { "grade": "RESEARCH", - "stale": false, - "code_sha": "c801bbda3ebfa6ff09259ed216ff8ba429552cf556670433f565fb67a76281d0", + "stale": true, + "code_sha": "b5b4a258db95b00de196f00604e246a2dad1f0137fb365d325d5fc75b1c96e2d", "reviewed_code_sha": "c801bbda3ebfa6ff09259ed216ff8ba429552cf556670433f565fb67a76281d0", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - "last_success_sha": "dfdecbe67", - "executed_at": "2026-09-18T22:51:57+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "30min", + "duree_estimee": "45min", "resource_cost": { "schema": 1, "execution": { - "class": "MODERATE", - "wall_seconds": 147.1, - "cells_timed": 9, - "cells_code": 9, + "class": "HEAVY", + "wall_seconds": 722.8, + "cells_timed": 17, + "cells_code": 17, "coverage": "FULL", "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 7, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-19", - "span_days": 61 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16698", - "cells_total": 24, - "cells_code": 9, - "cells_markdown": 15, - "cells_with_outputs": 6, + "issue_pr_associee": "#16231, #18649", + "cells_total": 36, + "cells_code": 17, + "cells_markdown": 19, + "cells_with_outputs": 12, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -25243,7 +25932,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-18-ArrowOfTimeReversibilization.ipynb", + "path": "IIT/ICT-Series/ICT-18-ArrowOfTimeReversibilization-Python.ipynb", "title": "ICT-18 -- Fleche du temps et reversibilisation (strate 5, Epic #4588)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25265,8 +25954,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "dfdecbe67", - "executed_at": "2026-09-18T22:51:57+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -25280,18 +25969,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 7, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-04", - "span_days": 76 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16698", + "issue_pr_associee": "#16231, #18649", "cells_total": 33, "cells_code": 14, "cells_markdown": 19, @@ -25304,7 +25993,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-18b-ReversibilityBudget.ipynb", + "path": "IIT/ICT-Series/ICT-18b-ReversibilityBudget-Python.ipynb", "title": "ICT-18b — Budget de réversibilité : la jambe « fin » de la réversibilisation", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25326,8 +26015,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "dfdecbe67", - "executed_at": "2026-09-18T22:51:57+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -25341,18 +26030,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 4, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-19", - "span_days": 61 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16698", + "issue_pr_associee": "#16231, #18649", "cells_total": 25, "cells_code": 8, "cells_markdown": 17, @@ -25365,7 +26054,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-19-EnjeuBattery.ipynb", + "path": "IIT/ICT-Series/ICT-19-EnjeuBattery-Python.ipynb", "title": "ICT-19 — La batterie de l'ENJEU : auto-maintien vs pur dissipateur", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25387,8 +26076,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "dfdecbe67", - "executed_at": "2026-09-18T22:51:57+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -25402,18 +26091,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 6, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-07", - "span_days": 73 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16698", + "issue_pr_associee": "#16231, #18649", "cells_total": 33, "cells_code": 11, "cells_markdown": 22, @@ -25426,7 +26115,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-19b-EnjeuBattery-Raffinement.ipynb", + "path": "IIT/ICT-Series/ICT-19b-EnjeuBattery-Raffinement-Python.ipynb", "title": "ICT-19b — Raffinement et résolution des stubs (tranche 3)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25448,8 +26137,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "012032c43", - "executed_at": "2026-09-22T23:10:20+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -25465,18 +26154,18 @@ ] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 4, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-19", - "span_days": 65 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-22", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17024", + "issue_pr_associee": "#16231, #18649", "cells_total": 25, "cells_code": 9, "cells_markdown": 16, @@ -25489,7 +26178,7 @@ "executable_locally": false }, { - "path": "IIT/ICT-Series/ICT-20-FeatureCatastrophes.ipynb", + "path": "IIT/ICT-Series/ICT-20-FeatureCatastrophes-Python.ipynb", "title": "ICT-20 — FeatureCatastrophes : *calibration de méthode*", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25511,8 +26200,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "bd34979b6", - "executed_at": "2026-09-18T22:52:04+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -25528,18 +26217,18 @@ ] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 7, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-03", - "span_days": 77 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16699", + "issue_pr_associee": "#16231, #18649", "cells_total": 30, "cells_code": 9, "cells_markdown": 21, @@ -25552,7 +26241,7 @@ "executable_locally": false }, { - "path": "IIT/ICT-Series/ICT-21-SAETrajectoires.ipynb", + "path": "IIT/ICT-Series/ICT-21-SAETrajectoires-Python.ipynb", "title": "ICT-21 — SAETrajectoires : le substrat S4 entre au banc", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25574,8 +26263,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "6f478c0e7", - "executed_at": "2026-09-25T18:31:56+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "1h", "resource_cost": { @@ -25591,18 +26280,18 @@ ] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 13, - "authors": 2, - "first_commit": "2026-07-07", - "span_days": 80 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-25", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#4362, #17807", + "issue_pr_associee": "#16231, #18649", "cells_total": 51, "cells_code": 20, "cells_markdown": 31, @@ -25615,8 +26304,8 @@ "executable_locally": false }, { - "path": "IIT/ICT-Series/ICT-21b-SAECalibration.ipynb", - "title": "ICT-21b-SAECalibration — que reconstruit réellement chaque SAE ?", + "path": "IIT/ICT-Series/ICT-21b-SAECalibration-Python.ipynb", + "title": "ICT-21b-SAECalibration-Python — que reconstruit réellement chaque SAE ?", "serie": "IIT", "sous_serie": "ICT-Series", "kernel": "Python 3", @@ -25637,8 +26326,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "6f478c0e7", - "executed_at": "2026-09-25T18:31:56+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -25654,18 +26343,18 @@ ] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 5, - "authors": 2, - "first_commit": "2026-08-31", - "span_days": 25 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-25", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#4362, #17807", + "issue_pr_associee": "#16231, #18649", "cells_total": 29, "cells_code": 11, "cells_markdown": 18, @@ -25678,8 +26367,8 @@ "executable_locally": false }, { - "path": "IIT/ICT-Series/ICT-21c-SAECatastrophes.ipynb", - "title": "ICT-21c-SAECatastrophes — forme et dynamique des perturbations du dictionnaire", + "path": "IIT/ICT-Series/ICT-21c-SAECatastrophes-Python.ipynb", + "title": "ICT-21c-SAECatastrophes-Python — forme et dynamique des perturbations du dictionnaire", "serie": "IIT", "sous_serie": "ICT-Series", "kernel": "Python 3", @@ -25700,8 +26389,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "6f478c0e7", - "executed_at": "2026-09-25T18:31:56+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -25717,18 +26406,18 @@ ] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 3, - "authors": 2, - "first_commit": "2026-08-31", - "span_days": 25 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-25", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#4362, #17807", + "issue_pr_associee": "#16231, #18649", "cells_total": 30, "cells_code": 12, "cells_markdown": 18, @@ -25741,7 +26430,7 @@ "executable_locally": false }, { - "path": "IIT/ICT-Series/ICT-22-LLMSubstrat.ipynb", + "path": "IIT/ICT-Series/ICT-22-LLMSubstrat-Python.ipynb", "title": "ICT-22 — LLMSubstrat : le transformer comme quatrième substrat du banc cross-substrat", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25763,8 +26452,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "bd34979b6", - "executed_at": "2026-09-18T22:52:04+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -25780,18 +26469,18 @@ ] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 3, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-07", - "span_days": 73 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16699", + "issue_pr_associee": "#16231, #18649", "cells_total": 26, "cells_code": 9, "cells_markdown": 17, @@ -25804,7 +26493,7 @@ "executable_locally": false }, { - "path": "IIT/ICT-Series/ICT-22b-CausalInterventionEngine.ipynb", + "path": "IIT/ICT-Series/ICT-22b-CausalInterventionEngine-Python.ipynb", "title": "ICT-22b -- Moteur d'intervention causal : operer, controler, mesurer — sur un banc ou la verite terrain est connue par construction", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25819,22 +26508,22 @@ "scientific_review_detail": { "grade": "RESEARCH", "stale": true, - "code_sha": "8611c340e2b72c76be33cd7f53399011f11fde3ff8b65d869d9f73aee2f08b3c", + "code_sha": "031b2313cc9dd7bd85d9c7284e2e2e978afe43d5d3c58cc1833fab48fde75b88", "reviewed_code_sha": "979d9d74381da4989af304a459232c5650235e8292419ea8630131e9feb06a43", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - "last_success_sha": "6f478c0e7", - "executed_at": "2026-09-25T18:31:56+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { "schema": 1, "execution": { "class": "LIGHT", - "wall_seconds": 29.1, + "wall_seconds": 37.8, "cells_timed": 15, "cells_code": 15, "coverage": "FULL", @@ -25844,18 +26533,18 @@ ] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 6, + "revisions": 1, "authors": 1, - "first_commit": "2026-09-12", - "span_days": 13 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-25", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#4362, #17807", + "issue_pr_associee": "#16231, #18649", "cells_total": 44, "cells_code": 15, "cells_markdown": 29, @@ -25868,7 +26557,7 @@ "executable_locally": false }, { - "path": "IIT/ICT-Series/ICT-23-PersonaCatastrophe.ipynb", + "path": "IIT/ICT-Series/ICT-23-PersonaCatastrophe-Python.ipynb", "title": "ICT-23 — PersonaCatastrophe : la fronce de Thom appliquee au desalignement emergent", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25890,8 +26579,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "bd34979b6", - "executed_at": "2026-09-18T22:52:04+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "15min", "resource_cost": { @@ -25905,18 +26594,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 6, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-04", - "span_days": 76 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16699", + "issue_pr_associee": "#16231, #18649", "cells_total": 20, "cells_code": 7, "cells_markdown": 13, @@ -25929,7 +26618,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-24-WorkspaceIgnition.ipynb", + "path": "IIT/ICT-Series/ICT-24-WorkspaceIgnition-Python.ipynb", "title": "ICT-24 — WorkspaceIgnition : l'axe Global Workspace et le Gate de réconciliation IIT<->GWT sur S4", "serie": "IIT", "sous_serie": "ICT-Series", @@ -25951,8 +26640,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "ed1e2c1da", - "executed_at": "2026-09-25T07:43:54+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -25968,18 +26657,18 @@ ] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 7, - "authors": 2, - "first_commit": "2026-07-10", - "span_days": 77 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-25", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17183, #17288", + "issue_pr_associee": "#16231, #18649", "cells_total": 24, "cells_code": 9, "cells_markdown": 15, @@ -25992,7 +26681,7 @@ "executable_locally": false }, { - "path": "IIT/ICT-Series/ICT-25-InoculationRL.ipynb", + "path": "IIT/ICT-Series/ICT-25-InoculationRL-Python.ipynb", "title": "ICT-25 — InoculationRL : GRPO à récompense *hackable*, inoculation de persona, et le pont ICTPostTraining", "serie": "IIT", "sous_serie": "ICT-Series", @@ -26014,8 +26703,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "f3e3dfa54", - "executed_at": "2026-09-27T06:14:24+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "1h", "resource_cost": { @@ -26032,18 +26721,18 @@ ] }, "creation": { - "class": "VERY_HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 36, - "authors": 2, - "first_commit": "2026-07-16", - "span_days": 73 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-27", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17999", + "issue_pr_associee": "#16231, #18649", "cells_total": 54, "cells_code": 20, "cells_markdown": 34, @@ -26056,7 +26745,7 @@ "executable_locally": false }, { - "path": "IIT/ICT-Series/ICT-26-SignalingConvention.ipynb", + "path": "IIT/ICT-Series/ICT-26-SignalingConvention-Python.ipynb", "title": "ICT-26 — Convention de signalisation (expérience A, strate 7)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -26078,8 +26767,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "1039eef67", - "executed_at": "2026-09-20T14:31:23+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -26093,18 +26782,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 5, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-29", - "span_days": 53 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-20", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16721", + "issue_pr_associee": "#16231, #18649", "cells_total": 23, "cells_code": 8, "cells_markdown": 15, @@ -26117,7 +26806,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-27-SymbolInvention.ipynb", + "path": "IIT/ICT-Series/ICT-27-SymbolInvention-Python.ipynb", "title": "ICT-27 — Invention de symboles (expérience B, strate 7)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -26139,8 +26828,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "07cd52bf2", - "executed_at": "2026-09-23T21:03:56+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -26154,18 +26843,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 5, - "authors": 2, - "first_commit": "2026-07-30", - "span_days": 55 + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-23", - "last_validator": "myia.ai.01.myia@gmail.com", - "issue_pr_associee": "#17040, #17463", + "last_validation": "2026-10-02", + "last_validator": "jsboige@gmail.com", + "issue_pr_associee": "#16231, #18649", "cells_total": 19, "cells_code": 8, "cells_markdown": 11, @@ -26178,7 +26867,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-28-CollectiveAdoption.ipynb", + "path": "IIT/ICT-Series/ICT-28-CollectiveAdoption-Python.ipynb", "title": "ICT-28 — Adoption collective et seuil de performativité (expérience C, strate 7)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -26200,8 +26889,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "5f429499f", - "executed_at": "2026-09-23T00:16:49+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -26215,18 +26904,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 8, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-30", - "span_days": 55 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-23", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17066, #17040, #17114", + "issue_pr_associee": "#16231, #18649", "cells_total": 23, "cells_code": 8, "cells_markdown": 15, @@ -26239,7 +26928,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-29-ConceptInoculation.ipynb", + "path": "IIT/ICT-Series/ICT-29-ConceptInoculation-Python.ipynb", "title": "ICT-29 — Inoculation d'un concept (expérience D, strate 7)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -26261,8 +26950,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "312169822", - "executed_at": "2026-09-22T09:16:29+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -26276,18 +26965,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 6, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-30", - "span_days": 54 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-22", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17066, #17040, #17115", + "issue_pr_associee": "#16231, #18649", "cells_total": 26, "cells_code": 8, "cells_markdown": 18, @@ -26300,7 +26989,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-30-InhibitedInvention.ipynb", + "path": "IIT/ICT-Series/ICT-30-InhibitedInvention-Python.ipynb", "title": "ICT-30 — Invention inhibée (expérience E, strate 7)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -26322,8 +27011,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "bd34979b6", - "executed_at": "2026-09-18T22:52:04+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -26337,18 +27026,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 3, + "revisions": 1, "authors": 1, - "first_commit": "2026-07-30", - "span_days": 50 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16682, #16699", + "issue_pr_associee": "#16231, #18649", "cells_total": 22, "cells_code": 8, "cells_markdown": 14, @@ -26361,7 +27050,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-31-ContrasteTroisSubstrats.ipynb", + "path": "IIT/ICT-Series/ICT-31-ContrasteTroisSubstrats-Python.ipynb", "title": "ICT-31 — Le contraste mesuré à trois substrats : bistable, Gray-Scott, Jeu de la Vie", "serie": "IIT", "sous_serie": "ICT-Series", @@ -26383,8 +27072,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "3bba6c092", - "executed_at": "2026-09-23T00:17:16+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -26398,18 +27087,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 6, + "revisions": 1, "authors": 1, - "first_commit": "2026-08-16", - "span_days": 38 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-23", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17066, #17040, #17119", + "issue_pr_associee": "#16231, #18649", "cells_total": 34, "cells_code": 14, "cells_markdown": 20, @@ -26422,7 +27111,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-32-StratificationCausaleLife.ipynb", + "path": "IIT/ICT-Series/ICT-32-StratificationCausaleLife-Python.ipynb", "title": "ICT-32 — Stratification causale du Jeu de la Vie : l'apportionment de Hoel sur substrat certifié", "serie": "IIT", "sous_serie": "ICT-Series", @@ -26444,8 +27133,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "8355b4466", - "executed_at": "2026-09-26T02:56:29+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -26459,18 +27148,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 5, + "revisions": 1, "authors": 1, - "first_commit": "2026-08-19", - "span_days": 38 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-26", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17040, #17060", + "issue_pr_associee": "#16231, #18649", "cells_total": 32, "cells_code": 12, "cells_markdown": 20, @@ -26483,7 +27172,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-33-SoupCollisions.ipynb", + "path": "IIT/ICT-Series/ICT-33-SoupCollisions-Python.ipynb", "title": "ICT-33 — Ensembles ouverts : soupes, collisions, et la mesure du bruit macro", "serie": "IIT", "sous_serie": "ICT-Series", @@ -26505,8 +27194,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "9bccdb6ee", - "executed_at": "2026-09-21T11:05:46+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -26520,18 +27209,18 @@ "external": [] }, "creation": { - 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(#14035, tranche 2)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -26743,26 +27432,26 @@ "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "RESEARCH", - "scientific_review_stale": false, + "scientific_review_stale": true, "scientific_review_detail": { "grade": "RESEARCH", - "stale": false, - "code_sha": "4bfea9bf8a989868b48734958d5346c01c69918af914c04ea12b356b73b6df64", + "stale": true, + "code_sha": "34d3c366e32811e8c5abb55f2ff6fc03acc0ebf155e245ec83b75b8c7c81e03f", "reviewed_code_sha": "4bfea9bf8a989868b48734958d5346c01c69918af914c04ea12b356b73b6df64", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - "last_success_sha": "9bccdb6ee", - "executed_at": "2026-09-21T11:05:46+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { "schema": 1, "execution": { "class": "MODERATE", - "wall_seconds": 112.3, + "wall_seconds": 102.1, "cells_timed": 9, "cells_code": 9, "coverage": "FULL", @@ -26771,16 +27460,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 2, + "revisions": 1, "authors": 1, - "first_commit": "2026-09-20", - "span_days": 1 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-21", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17026", + "issue_pr_associee": "#16231, #18649", "cells_total": 15, "cells_code": 9, "cells_markdown": 6, @@ -26793,7 +27482,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-35d-HumorTypologyBreakdown-SAE.ipynb", + "path": "IIT/ICT-Series/ICT-35d-HumorTypologyBreakdown-SAE-Python.ipynb", "title": "ICT-35d -- HumorTypologyBreakdown-SAE : le verdict survit-il à la forme de la blague ? (#14035, tranche finale)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -26808,22 +27497,22 @@ "scientific_review_detail": { "grade": "UNASSESSED", "stale": false, - "code_sha": "7a306f2a757766b9ca109662a836f0155613ac7aa28f80284cb3bb372a2507f4", + "code_sha": "73aacf81493aa0c5459eb66cac7e8481129c7e636b7c2c36127a7589a04702f7", "reviewed_code_sha": "", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - "last_success_sha": "bbd1ff47d", - "executed_at": "2026-09-24T09:00:22+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { "schema": 1, "execution": { "class": "MODERATE", - "wall_seconds": 143.9, + "wall_seconds": 123.9, "cells_timed": 11, "cells_code": 11, "coverage": "FULL", @@ -26836,14 +27525,14 @@ "history": "COMPLETE", "revisions": 1, "authors": 1, - "first_commit": "2026-09-24", + "first_commit": "2026-10-02", "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-24", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14035, #17587", + "issue_pr_associee": "#16231, #18649", "cells_total": 22, "cells_code": 11, "cells_markdown": 11, @@ -26856,7 +27545,7 @@ "executable_locally": false }, { - "path": "IIT/ICT-Series/ICT-36-FLens-FactoredGeometry.ipynb", + "path": "IIT/ICT-Series/ICT-36-FLens-FactoredGeometry-Python.ipynb", "title": "ICT-36 — F-Lens : mode factored-geometry, sous-espaces et additivite", "serie": "IIT", "sous_serie": "ICT-Series", @@ -26871,44 +27560,44 @@ "scientific_review_detail": { "grade": "RESEARCH", "stale": true, - "code_sha": "45224fe30f686f253f8a66884777d95533d6eb16a82c18265ecee9dd17ee3db8", + "code_sha": "5b3c54ad991c70aee1e67d1753defd8441a917990870162f48fe315894c5d847", "reviewed_code_sha": "c1da486357cf298755b24eeff56245494aa5e0c2ca2caa11de92abb17db09112", "reviewed_by": "", "peer": false, "sorry_free": false }, 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"cells_with_outputs": 11, + "issue_pr_associee": "#16231, #18649", + "cells_total": 36, + "cells_code": 16, + "cells_markdown": 20, + "cells_with_outputs": 13, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -26917,7 +27606,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-37-FLens-BeliefState.ipynb", + "path": "IIT/ICT-Series/ICT-37-FLens-BeliefState-Python.ipynb", "title": "ICT-37 - F-Lens : mode belief-state, probing lineaire et geometrie predictive held-out", "serie": "IIT", "sous_serie": "ICT-Series", @@ -26932,43 +27621,43 @@ "scientific_review_detail": { "grade": "RESEARCH", "stale": true, - "code_sha": "f3fb008a5683c921f4937f75bed4578df9edcaf26651d981c92db3c8ff17fba6", + "code_sha": "af2bcdbe78d93fecaa57168d5a3f74817b878865bde3476dceb96f4a80c3bf6d", "reviewed_code_sha": "2f70560d65c76788c5b256ffe867b2c222b498ba826c5baeffa28627d98f8f3a", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - 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"span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-25", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#4362, #17807", + "issue_pr_associee": "#16231, #18649", "cells_total": 37, "cells_code": 16, "cells_markdown": 21, @@ -27041,7 +27730,7 @@ "executable_locally": false }, { - "path": "IIT/ICT-Series/ICT-39-CompositionRegards.ipynb", + "path": "IIT/ICT-Series/ICT-39-CompositionRegards-Python.ipynb", "title": "ICT-39 — Composition de regards", "serie": "IIT", "sous_serie": "ICT-Series", @@ -27063,8 +27752,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "8355b4466", - "executed_at": "2026-09-26T02:56:29+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -27078,18 +27767,18 @@ "external": [] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": 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"forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -27141,18 +27830,18 @@ ] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 4, + "revisions": 1, "authors": 1, - "first_commit": "2026-09-18", - "span_days": 6 + "first_commit": "2026-10-02", + "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-24", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#15480, #17472", + "issue_pr_associee": "#16231, #18649", "cells_total": 28, "cells_code": 16, "cells_markdown": 12, @@ -27165,7 +27854,7 @@ "executable_locally": false }, { - "path": "IIT/ICT-Series/ICT-40b-AnalogCognitionWaves.ipynb", + "path": "IIT/ICT-Series/ICT-40b-AnalogCognitionWaves-Python.ipynb", "title": "ICT-40b — Cognition analogique : les ondes cérébrales comme substrat de calcul (Miller-Brincat-Roy 2026)", "serie": "IIT", "sous_serie": "ICT-Series", @@ -27187,8 +27876,8 @@ 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@@ -27289,7 +27978,7 @@ "executable_locally": true }, { - "path": "IIT/ICT-Series/ICT-42-Crosscoder-Distillation.ipynb", + "path": "IIT/ICT-Series/ICT-42-Crosscoder-Distillation-Python.ipynb", "title": "ICT-42 — Crosscoder : diffuser deux modèles, distilled reasoning vs base", "serie": "IIT", "sous_serie": "ICT-Series", @@ -27311,8 +28000,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "c9fa1982f", - "executed_at": "2026-09-24T12:07:10+02:00", + "last_success_sha": "6aa8452e7", + "executed_at": "2026-10-02T12:22:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -27332,17 +28021,17 @@ "history": "COMPLETE", "revisions": 1, "authors": 1, - "first_commit": "2026-09-24", + "first_commit": "2026-10-02", "span_days": 0 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-24", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16749, #16887", - "cells_total": 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graphe qu'on n'a pas", "serie": "Probas", "sous_serie": "DecisionTheory", "kernel": "Python (coursia-ml-training)", @@ -36722,8 +38029,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "10fb5074c", - "executed_at": "2026-09-23T20:47:17+02:00", + "last_success_sha": "c96fb1783", + "executed_at": "2026-10-02T08:15:08+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -36737,18 +38044,18 @@ "external": [] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 1, + "revisions": 3, "authors": 1, "first_commit": "2026-09-23", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2023", - "last_validation": "2026-09-23", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17416, #17421", + "issue_pr_associee": "#17421, #18720", "cells_total": 34, "cells_code": 12, "cells_markdown": 22, @@ -36762,7 +38069,7 @@ }, { "path": 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+ "executed_at": "2026-10-01T20:21:47+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -46698,16 +48066,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 9, + "revisions": 10, "authors": 3, "first_commit": "2026-03-19", - "span_days": 134 + "span_days": 196 } }, "owner_logique": "po-2026", - "last_validation": "2026-07-31", + "last_validation": "2026-10-01", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#8904, #8908", + "issue_pr_associee": "#14122, #18623", "cells_total": 22, "cells_code": 10, "cells_markdown": 12, @@ -46798,15 +48166,15 @@ "scientific_review_detail": { "grade": "UNASSESSED", "stale": false, - "code_sha": "ab344031d1a9b2262fb02e975877dce3d17a613ddf68f1a5567aa0c4444ba710", + "code_sha": "2c745bcd9733e4f018b4e6e114b606069b6766e864196e21c4115d23bef30b21", "reviewed_code_sha": "", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - 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"scientific_review_stale": false, "scientific_review_detail": { "grade": "UNASSESSED", "stale": false, - "code_sha": "c8d712f5887d4dac8805279f644787822d49dc631b151b300a40501377979c06", + "code_sha": "8d850e3907fae6d5826d9d68f7db87267e2958178b0beeced828b90e8f22a4ae", "reviewed_code_sha": "", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - "last_success_sha": "7ee48a5de", - "executed_at": "2026-09-26T01:13:52+02:00", + "last_success_sha": "ca5a7fe48", + "executed_at": "2026-09-27T18:20:06+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { "schema": 1, "execution": { - "class": "MODERATE", - "wall_seconds": 479.6, + "class": "HEAVY", + "wall_seconds": 906.1, "cells_timed": 13, "cells_code": 13, "coverage": "FULL", @@ -48515,16 +49883,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 5, + "revisions": 6, "authors": 1, "first_commit": "2026-08-29", - "span_days": 28 + "span_days": 29 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-26", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14446, #17733", + "issue_pr_associee": "#18042", "cells_total": 27, "cells_code": 13, "cells_markdown": 14, @@ -48559,8 +49927,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "2ba573760", - "executed_at": "2026-09-17T13:40:30+02:00", + "last_success_sha": "33cf07009", + "executed_at": "2026-09-28T10:39:19+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -48574,21 +49942,21 @@ "external": [] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 2, + "revisions": 3, "authors": 1, "first_commit": "2026-09-17", - "span_days": 0 + "span_days": 11 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-17", + "last_validation": "2026-09-28", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": 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"cells_code": 11, "cells_markdown": 14, @@ -48742,8 +50110,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "593db6a53", - "executed_at": "2026-09-23T20:57:52+02:00", + "last_success_sha": "37d9bb504", + "executed_at": "2026-10-01T16:16:39+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -48759,16 +50127,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-23", - "span_days": 0 + "span_days": 8 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-23", + "last_validation": "2026-10-01", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17573, #17575", + "issue_pr_associee": "#18421, #18429", "cells_total": 30, "cells_code": 11, "cells_markdown": 19, @@ -49049,8 +50417,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "f7aa71c99", - "executed_at": "2026-09-21T16:30:16+02:00", + 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+ "executed_at": "2026-09-29T03:50:17+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -54384,16 +55813,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-24", - "span_days": 0 + "span_days": 5 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-24", + "last_validation": "2026-09-29", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#13751, #17363", + "issue_pr_associee": "#17636, #18290", "cells_total": 35, "cells_code": 18, "cells_markdown": 17, @@ -54550,8 +55979,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "a0cf4d9a2", - "executed_at": "2026-09-06T17:06:13+02:00", + "last_success_sha": "37d9bb504", + "executed_at": "2026-10-01T16:16:39+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -54565,18 +55994,18 @@ "external": [] }, "creation": { - "class": 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- "last_validation": "2026-09-24", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#13751, #17363", + "issue_pr_associee": "#16231, #18634", "cells_total": 26, "cells_code": 8, "cells_markdown": 18, @@ -54855,8 +56284,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "494b9f41f", - "executed_at": "2026-09-18T22:41:51+02:00", + "last_success_sha": "d45329226", + "executed_at": "2026-10-01T16:22:51+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -54874,16 +56303,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 4, + "revisions": 5, "authors": 1, "first_commit": "2026-09-02", - "span_days": 16 + "span_days": 29 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", + "last_validation": "2026-10-01", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16705, #16677, #16707", + "issue_pr_associee": "#17636, #18543", 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"first_commit": "2026-09-06", - "span_days": 0 + "span_days": 25 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-06", + "last_validation": "2026-10-01", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14545, #14790", + "issue_pr_associee": "#18421, #18429", "cells_total": 44, "cells_code": 16, "cells_markdown": 28, @@ -55345,8 +56774,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "d2575da86", - "executed_at": "2026-09-26T21:14:17+02:00", + "last_success_sha": "37d9bb504", + "executed_at": "2026-10-01T16:16:39+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -55360,18 +56789,18 @@ "external": [] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 2, + "revisions": 3, "authors": 1, "first_commit": "2026-09-06", - "span_days": 20 + "span_days": 25 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-26", + "last_validation": "2026-10-01", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17967", + "issue_pr_associee": "#18421, #18429", "cells_total": 43, "cells_code": 16, "cells_markdown": 27, @@ -55589,8 +57018,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "a0cf4d9a2", - "executed_at": "2026-09-06T17:06:13+02:00", + "last_success_sha": "37d9bb504", + "executed_at": "2026-10-01T16:16:39+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -55606,16 +57035,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-06", - "span_days": 0 + "span_days": 25 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-06", + "last_validation": "2026-10-01", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14545, #14790", + "issue_pr_associee": "#18421, #18429", "cells_total": 47, "cells_code": 18, "cells_markdown": 29, @@ -55772,8 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"COMPLETE", - "revisions": 4, - "authors": 1, + "revisions": 5, + "authors": 2, "first_commit": "2026-07-10", - "span_days": 70 + "span_days": 79 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-18", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#11601, #16544", + "last_validation": "2026-09-27", + "last_validator": "jsboige+myia-po-2023@gmail.com", + "issue_pr_associee": "#15227, #18003", "cells_total": 22, "cells_code": 9, "cells_markdown": 13, @@ -56138,8 +57567,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "7e90a21b6", - "executed_at": "2026-08-04T07:09:28+02:00", + "last_success_sha": "fbd095f81", + "executed_at": "2026-09-27T20:37:32+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -56155,16 +57584,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 8, - "authors": 1, + "revisions": 9, + "authors": 2, "first_commit": "2026-07-10", - "span_days": 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"jsboige@gmail.com", - "issue_pr_associee": "#11601, #16546", + "last_validation": "2026-09-27", + "last_validator": "jsboige+myia-po-2023@gmail.com", + "issue_pr_associee": "#15227, #18003", "cells_total": 23, "cells_code": 9, "cells_markdown": 14, @@ -56321,8 +57750,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "155062ba3", - "executed_at": "2026-09-08T12:14:48+02:00", + "last_success_sha": "a9275631a", + "executed_at": "2026-10-01T16:16:57+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -56336,18 +57765,18 @@ "external": [] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 2, + "revisions": 3, "authors": 1, "first_commit": "2026-09-06", - "span_days": 2 + "span_days": 25 } }, "owner_logique": "po-2025", - "last_validation": "2026-09-08", + "last_validation": "2026-10-01", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14789, #15174", + 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"resource_cost": { @@ -72818,16 +74509,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 5, + "revisions": 6, "authors": 2, "first_commit": "2026-07-14", - "span_days": 54 + "span_days": 79 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-06", + "last_validation": "2026-10-01", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14169, #14829", + "issue_pr_associee": "#18421, #18429", "cells_total": 33, "cells_code": 14, "cells_markdown": 19, @@ -72923,8 +74614,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "b97198709", - "executed_at": "2026-09-11T10:40:18+02:00", + "last_success_sha": "f92765dee", + "executed_at": "2026-10-02T01:02:09+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -72940,16 +74631,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 4, + "revisions": 5, "authors": 1, "first_commit": "2026-07-14", - "span_days": 59 + "span_days": 80 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-11", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#15516, #15555", + "issue_pr_associee": "#16231, #18634", "cells_total": 32, "cells_code": 13, "cells_markdown": 19, @@ -73106,8 +74797,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "37d9bb504", + "executed_at": "2026-10-01T16:16:39+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -73123,16 +74814,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 3, + "revisions": 4, "authors": 2, "first_commit": "2026-07-14", - "span_days": 48 + "span_days": 79 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", + "last_validation": 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}, "production_signed": false, - "last_success_sha": "6ad49eb73", - "executed_at": "2026-07-14T04:47:44+02:00", + "last_success_sha": "a0aa4a3ca", + "executed_at": "2026-10-01T16:20:37+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -73306,16 +74997,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-07-14", - "span_days": 0 + "span_days": 79 } }, "owner_logique": "po-2024", - "last_validation": "2026-07-14", + "last_validation": "2026-10-01", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#6300, #6404", + "issue_pr_associee": "#17636, #18532", "cells_total": 22, "cells_code": 9, "cells_markdown": 13, @@ -73411,8 +75102,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "0e48c15fc", - "executed_at": "2026-08-10T10:12:06+02:00", + "last_success_sha": "37d9bb504", + "executed_at": "2026-10-01T16:16:39+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -73428,16 +75119,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 3, + "revisions": 5, "authors": 1, "first_commit": "2026-07-14", - "span_days": 27 + "span_days": 79 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-10", + "last_validation": "2026-10-01", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#9434, #10271", + "issue_pr_associee": "#18421, #18429", "cells_total": 16, "cells_code": 6, "cells_markdown": 10, @@ -73535,8 +75226,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "d72b7ec78", - "executed_at": "2026-08-21T16:40:58+02:00", + "last_success_sha": "c42e5f76f", + "executed_at": "2026-09-29T19:34:49+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -73552,16 +75243,16 @@ "creation": { "class": "HEAVY", "history": "COMPLETE", - "revisions": 14, + "revisions": 15, "authors": 1, "first_commit": "2026-02-21", - "span_days": 181 + "span_days": 220 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-21", + "last_validation": "2026-09-29", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#11962, #12010", + "issue_pr_associee": "#17636, #18316", "cells_total": 22, "cells_code": 5, "cells_markdown": 17, @@ -73657,8 +75348,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "f70a84287", - "executed_at": "2026-08-23T00:45:52+02:00", + "last_success_sha": "c42e5f76f", + "executed_at": "2026-09-29T19:34:49+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -73674,16 +75365,16 @@ "creation": { "class": "HEAVY", "history": "COMPLETE", - "revisions": 25, + "revisions": 26, "authors": 1, "first_commit": "2026-02-21", - "span_days": 183 + "span_days": 220 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-23", + "last_validation": "2026-09-29", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#12365, #12372", + "issue_pr_associee": "#17636, #18316", "cells_total": 75, "cells_code": 23, "cells_markdown": 52, @@ -73703,30 +75394,30 @@ "kernel": ".NET (C#)", "status": "READY", "pedagogical_role": "", - "maturity": "BETA", - "editorial": "BETA", + "maturity": "ALPHA", + "editorial": "ALPHA", "reproducibility": "EXECUTED", "scientific_review": "UNASSESSED", "scientific_review_stale": false, "scientific_review_detail": { "grade": "UNASSESSED", "stale": false, - "code_sha": "2799a2cf7ca7da8270dd1069101126b59b59675c4f1f8d1fd5d32b16d1caf42b", + "code_sha": "56b2fe76129898b3301697d5778bef868306d926efe99042806e3aaa23c46457", "reviewed_code_sha": "", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - "last_success_sha": "fc466081f", - "executed_at": "2026-09-26T12:55:42+02:00", + "last_success_sha": "e327f8712", + "executed_at": "2026-10-02T08:16:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { "schema": 1, "execution": { "class": "LIGHT", - "wall_seconds": 2.4, + "wall_seconds": 4.9, "cells_timed": 15, "cells_code": 15, "coverage": "FULL", @@ -73735,19 +75426,19 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 5, + "revisions": 6, "authors": 1, "first_commit": "2026-07-08", - "span_days": 80 + "span_days": 86 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-26", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17040, #17059", - "cells_total": 42, + "issue_pr_associee": "#18703, #18699, #18726", + "cells_total": 46, "cells_code": 15, - "cells_markdown": 27, + "cells_markdown": 31, "cells_with_outputs": 15, "cells_without_outputs": 0, "requires_api": false, @@ -73903,8 +75594,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "467150605", - "executed_at": "2026-08-28T01:52:13+02:00", + "last_success_sha": "6567611fa", + "executed_at": "2026-10-02T04:36:03+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "1h", "resource_cost": { @@ -73920,19 +75611,19 @@ "creation": { "class": "VERY_HEAVY", "history": "COMPLETE", - "revisions": 45, + "revisions": 47, "authors": 2, "first_commit": "2026-02-21", - "span_days": 188 + "span_days": 223 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-28", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#11601, #12787", - "cells_total": 93, + "issue_pr_associee": "#17040, #18689", + "cells_total": 89, "cells_code": 31, - "cells_markdown": 62, + "cells_markdown": 58, "cells_with_outputs": 25, "cells_without_outputs": 0, "requires_api": false, @@ -74086,8 +75777,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "fc466081f", - "executed_at": "2026-09-26T12:55:42+02:00", + "last_success_sha": "4c808b30c", + "executed_at": "2026-09-26T21:17:11+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -74103,7 +75794,7 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 4, + "revisions": 6, "authors": 1, "first_commit": "2026-09-01", "span_days": 25 @@ -74147,8 +75838,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "95c804ac6", - "executed_at": "2026-09-23T03:25:18+02:00", + "last_success_sha": "c42e5f76f", + "executed_at": "2026-09-29T19:34:49+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -74162,18 +75853,18 @@ "external": [] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 2, + "revisions": 3, "authors": 1, "first_commit": "2026-09-20", - "span_days": 3 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-23", + "last_validation": "2026-09-29", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17037", + "issue_pr_associee": "#17636, #18316", "cells_total": 43, "cells_code": 15, "cells_markdown": 28, @@ -74637,8 +76328,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "1467cb616", - "executed_at": "2026-09-14T13:05:01+02:00", + "last_success_sha": "a0aa4a3ca", + "executed_at": "2026-10-01T16:20:37+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -74656,16 +76347,16 @@ "creation": { "class": "HEAVY", "history": "COMPLETE", - "revisions": 21, + "revisions": 22, "authors": 2, "first_commit": "2026-02-21", - "span_days": 205 + "span_days": 222 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-14", + "last_validation": "2026-10-01", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#13410, #16035", + "issue_pr_associee": "#17636, #18532", "cells_total": 53, "cells_code": 18, "cells_markdown": 35, @@ -74822,8 +76513,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "b3bea5003", - "executed_at": "2026-09-18T22:50:55+02:00", + "last_success_sha": "c161071c6", + "executed_at": "2026-10-02T04:23:22+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -74839,16 +76530,16 @@ "creation": { "class": "HEAVY", "history": "COMPLETE", - "revisions": 15, + "revisions": 16, "authors": 1, "first_commit": "2026-02-21", - "span_days": 209 + "span_days": 223 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16472, #16527", + "issue_pr_associee": "#17782, #18707", "cells_total": 37, "cells_code": 12, "cells_markdown": 25, @@ -74883,8 +76574,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "fc8da0912", - "executed_at": "2026-09-18T17:17:17+02:00", + "last_success_sha": "c161071c6", + "executed_at": "2026-10-02T04:23:22+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -74902,19 +76593,19 @@ "creation": { "class": "HEAVY", "history": "COMPLETE", - "revisions": 20, + "revisions": 21, "authors": 2, "first_commit": "2026-02-21", - "span_days": 209 + "span_days": 223 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#15611, #16042", - "cells_total": 48, + "issue_pr_associee": "#17782, #18707", + "cells_total": 47, "cells_code": 18, - "cells_markdown": 30, + "cells_markdown": 29, "cells_with_outputs": 11, "cells_without_outputs": 0, "requires_api": true, @@ -75129,8 +76820,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "b91f8ff4e", - "executed_at": "2026-09-22T09:20:08+02:00", + "last_success_sha": "6567611fa", + "executed_at": "2026-10-02T04:36:03+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "1h", "resource_cost": { @@ -75146,19 +76837,19 @@ "creation": { "class": "HEAVY", "history": "COMPLETE", - "revisions": 27, + "revisions": 28, "authors": 2, "first_commit": "2026-02-21", - "span_days": 213 + "span_days": 223 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-22", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17066, #17133", - "cells_total": 110, + "issue_pr_associee": "#17040, #18689", + "cells_total": 107, "cells_code": 37, - "cells_markdown": 73, + "cells_markdown": 70, "cells_with_outputs": 33, "cells_without_outputs": 0, "requires_api": false, @@ -75168,8 +76859,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/00-Foundations/SC-0-Cypherpunk-Origins.ipynb", - "title": "SC-0-Cypherpunk-Origins - Les origines Cypherpunk de la blockchain", + "path": "SymbolicAI/SmartContracts/00-Foundations/SC-00-Cypherpunk-Origins-Python.ipynb", + "title": "SC-00-Cypherpunk-Origins-Python - Les origines Cypherpunk de la blockchain", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -75190,8 +76881,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "e755c8317", - "executed_at": "2026-09-22T19:59:51+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -75205,18 +76896,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 22, + "revisions": 1, "authors": 1, - "first_commit": "2026-03-17", - "span_days": 189 + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-22", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17066, #17128", + "issue_pr_associee": "#16231, #17837", "cells_total": 41, "cells_code": 15, "cells_markdown": 26, @@ -75229,8 +76920,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/00-Foundations/SC-1-Setup-Foundry.ipynb", - "title": "SC-1-Setup-Foundry - Environnement Smart Contracts", + "path": "SymbolicAI/SmartContracts/00-Foundations/SC-01-Setup-Foundry-Python.ipynb", + "title": "SC-01-Setup-Foundry-Python - Environnement Smart Contracts", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -75251,8 +76942,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "6d912bb29", - "executed_at": "2026-09-05T12:11:16+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "15min", "resource_cost": { @@ -75266,18 +76957,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 19, + "revisions": 1, "authors": 1, - "first_commit": "2026-03-17", - "span_days": 172 + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-05", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#9434, #14717", + "issue_pr_associee": "#16231, #17837", "cells_total": 26, "cells_code": 7, "cells_markdown": 19, @@ -75290,8 +76981,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/00-Foundations/SC-2-Setup-Web3py.ipynb", - "title": "SC-2-Setup-Web3py - Python et la Blockchain", + "path": "SymbolicAI/SmartContracts/00-Foundations/SC-02-Setup-Web3py-Python.ipynb", + "title": "SC-02-Setup-Web3py-Python - Python et la Blockchain", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -75312,8 +77003,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "5132e7ab9", - "executed_at": "2026-09-22T09:20:57+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -75327,18 +77018,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 23, + "revisions": 1, "authors": 1, - "first_commit": "2026-03-17", - "span_days": 189 + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-22", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17066, #17138", + "issue_pr_associee": "#16231, #17837", "cells_total": 34, "cells_code": 12, "cells_markdown": 22, @@ -75351,7 +77042,7 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/00-Foundations/SC-2b-Bac-ASable-Institutionnel.ipynb", + "path": "SymbolicAI/SmartContracts/00-Foundations/SC-02b-Bac-ASable-Institutionnel-Python.ipynb", "title": "SC-2b - Bac a sable institutionnel : des acteurs, pas seulement des contrats", "serie": "SymbolicAI", "sous_serie": "SmartContracts", @@ -75373,8 +77064,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "a41b8fc07", - "executed_at": "2026-09-22T04:56:39+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -75390,18 +77081,18 @@ ] }, "creation": { - "class": "MODERATE", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 3, - "authors": 2, - "first_commit": "2026-09-01", - "span_days": 21 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-22", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#16919, #16935", + "last_validation": "2026-09-27", + "last_validator": "jsboige@gmail.com", + "issue_pr_associee": "#16231, #17837", "cells_total": 41, "cells_code": 18, "cells_markdown": 23, @@ -75414,8 +77105,8 @@ "executable_locally": false }, { - "path": "SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-3-Solidity-Basics.ipynb", - "title": "SC-3-Solidity-Basics - Fondements de Solidity", + "path": "SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-03-Solidity-Basics-Python.ipynb", + "title": "SC-03-Solidity-Basics-Python - Fondements de Solidity", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": ".venv", @@ -75436,8 +77127,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "d4e31c7a1", - "executed_at": "2026-08-18T15:47:16+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -75451,18 +77142,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 24, - "authors": 3, - "first_commit": "2026-03-17", - "span_days": 154 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-18", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#10923, #11641", + "issue_pr_associee": "#16231, #17837", "cells_total": 51, "cells_code": 18, "cells_markdown": 33, @@ -75475,8 +77166,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-4-Functions-State.ipynb", - "title": "SC-4-Functions-State - Fonctions et État", + "path": "SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-04-Functions-State-Python.ipynb", + "title": "SC-04-Functions-State-Python - Fonctions et État", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -75497,8 +77188,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "5064187dd", - "executed_at": "2026-09-05T12:44:02+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -75512,18 +77203,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 23, - "authors": 2, - "first_commit": "2026-03-17", - "span_days": 172 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-05", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14209, #14716", + "issue_pr_associee": "#16231, #17837", "cells_total": 42, "cells_code": 15, "cells_markdown": 27, @@ -75536,8 +77227,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-5-Inheritance.ipynb", - "title": "SC-5-Inheritance - Heritage et Interfaces", + "path": "SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-05-Inheritance-Python.ipynb", + "title": "SC-05-Inheritance-Python - Heritage et Interfaces", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -75558,8 +77249,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "5064187dd", - "executed_at": "2026-09-05T12:44:02+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -75573,18 +77264,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 23, - "authors": 2, - "first_commit": "2026-03-17", - "span_days": 172 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-05", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14209, #14716", + "issue_pr_associee": "#16231, #17837", "cells_total": 38, "cells_code": 12, "cells_markdown": 26, @@ -75597,8 +77288,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-6-Errors-Events.ipynb", - "title": "SC-6-Errors-Events - Erreurs et Événements", + "path": "SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-06-Errors-Events-Python.ipynb", + "title": "SC-06-Errors-Events-Python - Erreurs et Événements", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -75619,8 +77310,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "38888f0af", - "executed_at": "2026-09-20T00:46:11+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -75634,18 +77325,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 30, - "authors": 3, - "first_commit": "2026-03-17", - "span_days": 187 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-20", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16762, #16788", + "issue_pr_associee": "#16231, #17837", "cells_total": 33, "cells_code": 11, "cells_markdown": 22, @@ -75658,8 +77349,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-10-Account-Abstraction.ipynb", - "title": "SC-10-Account-Abstraction - ERC-4337 v0.9", + "path": "SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-07-Token-Standards-Python.ipynb", + "title": "SC-07-Token-Standards-Python - Standards de Tokens", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -75673,43 +77364,43 @@ "scientific_review_detail": { "grade": "UNASSESSED", "stale": false, - "code_sha": "96b71187217d7806d47a8ca7f0e79d9b7ab294a3430db6b67a48b1cea4b100af", + "code_sha": "a1238d2e90cb8f03b351dd83ab8726c0618feb693670dcd7e6743047d90cfb67", "reviewed_code_sha": 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"production_signed": false, - "last_success_sha": "d4e31c7a1", - "executed_at": "2026-08-18T15:47:16+02:00", + "last_success_sha": "6567611fa", + "executed_at": "2026-10-02T04:36:03+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -76254,21 +77945,21 @@ ] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 23, - "authors": 2, - "first_commit": "2026-03-17", - "span_days": 154 + "revisions": 2, + "authors": 1, + "first_commit": "2026-09-27", + "span_days": 5 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#10923, #11641", - "cells_total": 30, + "issue_pr_associee": "#17040, #18689", + "cells_total": 29, "cells_code": 11, - "cells_markdown": 19, + "cells_markdown": 18, "cells_with_outputs": 10, "cells_without_outputs": 0, "requires_api": true, @@ -76278,8 +77969,8 @@ "executable_locally": false }, { - "path": "SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-15-Zero-Knowledge-Proofs.ipynb", - "title": "SC-15-Zero-Knowledge-Proofs - Preuves a Divulgation Nulle", + "path": "SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-15-Zero-Knowledge-Proofs-Python.ipynb", + "title": "SC-15-Zero-Knowledge-Proofs-Python - Preuves a Divulgation Nulle", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -76300,8 +77991,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "d4e31c7a1", - "executed_at": "2026-08-18T15:47:16+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -76315,18 +78006,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 24, - "authors": 2, - "first_commit": "2026-03-17", - "span_days": 154 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-18", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#10923, #11641", + "issue_pr_associee": "#16231, #17837", "cells_total": 45, "cells_code": 15, "cells_markdown": 30, @@ -76339,8 +78030,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-16-Homomorphic-Encryption.ipynb", - "title": "SC-16-Homomorphic-Encryption - Chiffrement Homomorphique", + "path": "SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-16-Homomorphic-Encryption-Python.ipynb", + "title": "SC-16-Homomorphic-Encryption-Python - Chiffrement Homomorphique", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3 (SC-16 Concrete, WSL)", @@ -76361,8 +78052,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "d4e31c7a1", - "executed_at": "2026-08-18T15:47:16+02:00", + "last_success_sha": "6567611fa", + "executed_at": "2026-10-02T04:36:03+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -76376,21 +78067,21 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 31, + "revisions": 2, "authors": 1, - "first_commit": "2026-03-17", - "span_days": 154 + "first_commit": "2026-09-27", + "span_days": 5 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#10923, #11641", - "cells_total": 44, + "issue_pr_associee": "#17040, #18689", + "cells_total": 42, "cells_code": 13, - "cells_markdown": 31, + "cells_markdown": 29, "cells_with_outputs": 10, "cells_without_outputs": 0, "requires_api": false, @@ -76400,8 +78091,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-17-E2E-Verifiable-Voting.ipynb", - "title": "SC-17-E2E-Verifiable-Voting - Vote Electronique Verifiable", + "path": "SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-17-E2E-Verifiable-Voting-Python.ipynb", + "title": "SC-17-E2E-Verifiable-Voting-Python - Vote Electronique Verifiable", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -76422,8 +78113,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "c62c7bbc5", - "executed_at": "2026-09-22T09:21:12+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -76437,18 +78128,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 24, + "revisions": 1, "authors": 1, - "first_commit": "2026-03-17", - "span_days": 189 + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-22", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17066, #17139", + "issue_pr_associee": "#16231, #17837", "cells_total": 37, "cells_code": 12, "cells_markdown": 25, @@ -76461,8 +78152,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/05-Alternative-Chains/SC-18-Vyper.ipynb", - "title": "SC-18-Vyper - Smart Contracts en Python-like", + "path": "SymbolicAI/SmartContracts/05-Alternative-Chains/SC-18-Vyper-Python.ipynb", + "title": "SC-18-Vyper-Python - Smart Contracts en Python-like", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -76483,8 +78174,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "d4e31c7a1", - "executed_at": "2026-08-18T15:47:16+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -76498,18 +78189,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 23, + "revisions": 1, "authors": 1, - "first_commit": "2026-03-17", - "span_days": 154 + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-18", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#10923, #11641", + "issue_pr_associee": "#16231, #17837", "cells_total": 34, "cells_code": 11, "cells_markdown": 23, @@ -76522,8 +78213,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/05-Alternative-Chains/SC-19-Ripple-XRP.ipynb", - "title": "SC-19-Ripple-XRP - Protocole Ripple et XRP Ledger", + "path": "SymbolicAI/SmartContracts/05-Alternative-Chains/SC-19-Ripple-XRP-Python.ipynb", + "title": "SC-19-Ripple-XRP-Python - Protocole Ripple et XRP Ledger", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3 (smartcontracts)", @@ -76544,8 +78235,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "6567611fa", + "executed_at": "2026-10-02T04:36:03+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -76559,21 +78250,21 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 26, - "authors": 2, - "first_commit": "2026-03-17", - "span_days": 167 + "revisions": 2, + "authors": 1, + "first_commit": "2026-09-27", + "span_days": 5 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", - "cells_total": 45, + "last_validation": "2026-10-02", + "last_validator": "jsboige@gmail.com", + "issue_pr_associee": "#17040, #18689", + "cells_total": 42, "cells_code": 13, - "cells_markdown": 32, + "cells_markdown": 29, "cells_with_outputs": 12, "cells_without_outputs": 0, "requires_api": false, @@ -76583,8 +78274,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/05-Alternative-Chains/SC-20-Bitcoin-Scripting.ipynb", - "title": "SC-20-Bitcoin-Scripting - Bitcoin, UTXO et Scripts", + "path": "SymbolicAI/SmartContracts/05-Alternative-Chains/SC-20-Bitcoin-Scripting-Python.ipynb", + "title": "SC-20-Bitcoin-Scripting-Python - Bitcoin, UTXO et Scripts", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": ".venv", @@ -76605,8 +78296,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "5064187dd", - "executed_at": "2026-09-05T12:44:02+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -76622,18 +78313,18 @@ ] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 25, + "revisions": 1, "authors": 1, - "first_commit": "2026-03-17", - "span_days": 172 + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-05", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14209, #14716", + "issue_pr_associee": "#16231, #17837", "cells_total": 42, "cells_code": 14, "cells_markdown": 28, @@ -76646,8 +78337,8 @@ "executable_locally": false }, { - "path": "SymbolicAI/SmartContracts/05-Alternative-Chains/SC-21-Move-Sui.ipynb", - "title": "SC-21-Move-Sui - Move sur Sui", + "path": "SymbolicAI/SmartContracts/05-Alternative-Chains/SC-21-Move-Sui-Python.ipynb", + "title": "SC-21-Move-Sui-Python - Move sur Sui", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -76668,8 +78359,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "d4e31c7a1", - "executed_at": "2026-08-18T15:47:16+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -76683,18 +78374,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 15, - "authors": 3, - "first_commit": "2026-03-17", - "span_days": 154 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-18", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#10923, #11641", + "issue_pr_associee": "#16231, #17837", "cells_total": 25, "cells_code": 8, "cells_markdown": 17, @@ -76707,8 +78398,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/05-Alternative-Chains/SC-22-Solana-Anchor.ipynb", - "title": "SC-22-Solana-Anchor - Solana avec Anchor", + "path": "SymbolicAI/SmartContracts/05-Alternative-Chains/SC-22-Solana-Anchor-Python.ipynb", + "title": "SC-22-Solana-Anchor-Python - Solana avec Anchor", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -76729,8 +78420,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "766a9100d", - "executed_at": "2026-09-06T17:39:32+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -76744,18 +78435,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 22, - "authors": 2, - "first_commit": "2026-03-17", - "span_days": 173 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-06", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14817, #14854", + "issue_pr_associee": "#16231, #17837", "cells_total": 37, "cells_code": 13, "cells_markdown": 24, @@ -76768,8 +78459,8 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/06-Real-World/SC-23-Cross-Chain.ipynb", - "title": "SC-23-Cross-Chain - Interoperabilite Cross-Chain", + "path": "SymbolicAI/SmartContracts/06-Real-World/SC-23-Cross-Chain-Python.ipynb", + "title": "SC-23-Cross-Chain-Python - Interoperabilite Cross-Chain", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -76783,15 +78474,15 @@ "scientific_review_detail": { "grade": "UNASSESSED", "stale": false, - "code_sha": "5acbcf2802b3ee96dfce30d037ebfdc9362f1beb1641f4771fa2202d56b26b0d", + "code_sha": "a37e743b1518386c02cc9b3d8faf5ae4af9af98f71b56ec00ba95ff4507fde10", "reviewed_code_sha": "", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - "last_success_sha": "6e949878b", - "executed_at": "2026-09-25T15:37:06+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -76805,18 +78496,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 22, + "revisions": 1, "authors": 1, - "first_commit": "2026-03-17", - "span_days": 192 + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-25", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17498, #17745", + "issue_pr_associee": "#16231, #17837", "cells_total": 32, "cells_code": 11, "cells_markdown": 21, @@ -76829,7 +78520,7 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/06-Real-World/SC-24-Testnet-Deploy.ipynb", + "path": "SymbolicAI/SmartContracts/06-Real-World/SC-24-Testnet-Deploy-Python.ipynb", "title": "SC-24 : Deploiement sur Testnets", "serie": "SymbolicAI", "sous_serie": "SmartContracts", @@ -76851,8 +78542,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "6e949878b", - "executed_at": "2026-09-25T15:37:06+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -76866,18 +78557,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 23, + "revisions": 1, "authors": 1, - "first_commit": "2026-03-17", - "span_days": 192 + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-25", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17498, #17745", + "issue_pr_associee": "#16231, #17837", "cells_total": 38, "cells_code": 12, "cells_markdown": 26, @@ -76890,7 +78581,7 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/06-Real-World/SC-25-Mainnet-Deploy.ipynb", + "path": "SymbolicAI/SmartContracts/06-Real-World/SC-25-Mainnet-Deploy-Python.ipynb", "title": "SC-25 : Deploiement Mainnet (L2)", "serie": "SymbolicAI", "sous_serie": "SmartContracts", @@ -76912,8 +78603,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "d4e31c7a1", - "executed_at": "2026-08-18T15:47:16+02:00", + "last_success_sha": "6567611fa", + "executed_at": "2026-10-02T04:36:03+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -76927,21 +78618,21 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 21, + "revisions": 3, "authors": 1, - "first_commit": "2026-03-17", - "span_days": 154 + "first_commit": "2026-09-27", + "span_days": 5 } }, "owner_logique": "po-2024", - "last_validation": "2026-08-18", + "last_validation": "2026-10-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#10923, #11641", - "cells_total": 26, + "issue_pr_associee": "#17040, #18689", + "cells_total": 24, "cells_code": 8, - "cells_markdown": 18, + "cells_markdown": 16, "cells_with_outputs": 4, "cells_without_outputs": 0, "requires_api": false, @@ -76951,7 +78642,7 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/06-Real-World/SC-26-Final-Project.ipynb", + "path": "SymbolicAI/SmartContracts/06-Real-World/SC-26-Final-Project-Python.ipynb", "title": "SC-26 : Projet Final - DApp Complete", "serie": "SymbolicAI", "sous_serie": "SmartContracts", @@ -76973,8 +78664,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "c29574410", - "executed_at": "2026-09-13T00:40:50+02:00", + "last_success_sha": "c94f91ed0", + "executed_at": "2026-09-27T18:56:53+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "15min", "resource_cost": { @@ -76988,18 +78679,18 @@ "external": [] }, "creation": { - "class": "HEAVY", + "class": "LIGHT", "history": "COMPLETE", - "revisions": 20, - "authors": 2, - "first_commit": "2026-03-17", - "span_days": 180 + "revisions": 1, + "authors": 1, + "first_commit": "2026-09-27", + "span_days": 0 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-13", + "last_validation": "2026-09-27", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#15719, #15792", + "issue_pr_associee": "#16231, #17837", "cells_total": 29, "cells_code": 5, "cells_markdown": 24, @@ -77012,7 +78703,7 @@ "executable_locally": true }, { - "path": "SymbolicAI/SmartContracts/06-Real-World/SC-27-Dette-Irreversibilite.ipynb", + "path": "SymbolicAI/SmartContracts/06-Real-World/SC-27-Dette-Irreversibilite-Python.ipynb", "title": "SC-27 : Dette d'irréversibilité — la boucle de gouvernance, mesurée", "serie": "SymbolicAI", "sous_serie": "SmartContracts", @@ -77034,8 +78725,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "5efc320f3", - "executed_at": 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b/COURSE_CATALOG.generated.md @@ -5,22 +5,22 @@ # CoursIA Notebook Catalog -Total notebooks: 1312 +Total notebooks: 1340 ## Status Summary -- **BROKEN**: 3 -- **DEMO**: 198 -- **READY**: 1111 -- **TOTAL**: 1312 +- **BROKEN**: 2 +- **DEMO**: 201 +- **READY**: 1137 +- **TOTAL**: 1340 ## Maturity Summary -- **ALPHA**: 64 -- **BETA**: 1160 -- **DRAFT**: 84 +- **ALPHA**: 68 +- **BETA**: 1179 +- **DRAFT**: 89 - **TEMPLATE**: 4 -- **TOTAL**: 1312 +- **TOTAL**: 1340 ## Series / Sub-series Totals @@ -30,32 +30,32 @@ Total notebooks: 1312 | GenAI | Audio | 38 | | GenAI | CaseStudies | 5 | | GenAI | FallacyDetection | 5 | -| GenAI | FineTuning | 10 | +| GenAI | FineTuning | 11 | | GenAI | Image | 21 | | GenAI | Integrations-DotNet | 15 | | GenAI | Plateformes-Conversationnelles | 28 | | GenAI | PostTraining | 20 | | GenAI | RAG-et-Memoire-Semantique | 10 | -| GenAI | Security | 5 | -| GenAI | SemanticKernel | 20 | -| GenAI | Texte | 34 | +| GenAI | Security | 6 | +| GenAI | SemanticKernel | 21 | +| GenAI | Texte | 41 | | GenAI | Vibe-Coding | 8 | | GenAI | Video | 22 | | Search | Applications | 59 | +| Search | Discrepancy | 1 | | Search | Part1-Foundations | 43 | | Search | Part2-CSP | 18 | | Search | Part4-Metaheuristics | 35 | -| ML | DataScienceWithAgents | 97 | +| ML | DataScienceWithAgents | 103 | | ML | ML.Net | 23 | | SymbolicAI | Racine | 1 | -| SymbolicAI | Argument_Analysis | 36 | -| SymbolicAI | Geometry | 4 | -| SymbolicAI | Lean | 71 | +| SymbolicAI | Argument_Analysis | 32 | +| SymbolicAI | Lean | 82 | | SymbolicAI | Planners | 25 | | SymbolicAI | SemanticWeb | 28 | | SymbolicAI | SmartContracts | 31 | -| SymbolicAI | SMT | 46 | -| SymbolicAI | SymbolicLearning | 26 | +| SymbolicAI | SMT | 47 | +| SymbolicAI | SymbolicLearning | 27 | | SymbolicAI | Tweety | 39 | | QuantConnect | kelly_lean | 2 | | QuantConnect | ML-Training-Pipeline | 4 | @@ -64,24 +64,25 @@ Total notebooks: 1312 | GameTheory | Racine | 99 | | GameTheory | SocialChoice | 10 | | Sudoku | Racine | 38 | -| Probas | Applications | 3 | +| Probas | Applications | 4 | | Probas | DecisionTheory | 31 | | Probas | Infer | 21 | -| Probas | PyMC | 19 | +| Probas | PyMC | 20 | | IIT | Racine | 6 | -| IIT | ICT-Series | 84 | +| IIT | ICT-Series | 87 | | RL | Racine | 36 | | CaseStudies | Diagnostic-Medical | 2 | | CaseStudies | Oncology-Planning | 2 | | CaseStudies | SmartGrid-Energy | 2 | | Complexity | Racine | 9 | +| Compression | Racine | 1 | | NLP | Racine | 5 | | cross-series | socle-metadata-driven | 1 | -| **TOTAL** | | **1312** | +| **TOTAL** | | **1340** | ## By Series -### GenAI (247 notebooks) — BROKEN:2, DEMO:121, READY:124 | ALPHA:21, BETA:208, DRAFT:15, TEMPLATE:3 +### GenAI (257 notebooks) — BROKEN:2, DEMO:124, READY:131 | ALPHA:21, BETA:217, DRAFT:16, TEMPLATE:3 #### 00-GenAI-Environment (6) @@ -99,7 +100,7 @@ Total notebooks: 1312 | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| | 1 | [01-1-OpenAI-TTS-Intro.ipynb](MyIA.AI.Notebooks/GenAI/Audio/01-Foundation/01-1-OpenAI-TTS-Intro.ipynb) | OpenAI TTS - Synthese Vocale par API | Python 3 | DEMO | BETA | 45min | po-2025 | -| 2 | [01-2-OpenAI-Whisper-STT.ipynb](MyIA.AI.Notebooks/GenAI/Audio/01-Foundation/01-2-OpenAI-Whisper-STT.ipynb) | OpenAI Whisper STT - Reconnaissance Vocale par API | Python 3 | DEMO | BETA | 45min | po-2025 | +| 2 | [01-2-OpenAI-Whisper-STT.ipynb](MyIA.AI.Notebooks/GenAI/Audio/01-Foundation/01-2-OpenAI-Whisper-STT.ipynb) | OpenAI Whisper STT - Reconnaissance Vocale par API | .venv (3.12.14) | DEMO | BETA | 45min | po-2025 | | 3 | [01-3-Basic-Audio-Operations.ipynb](MyIA.AI.Notebooks/GenAI/Audio/01-Foundation/01-3-Basic-Audio-Operations.ipynb) | Opérations de Base sur l'Audio | Python 3 | DEMO | BETA | 45min | po-2025 | | 4 | [01-4-Whisper-Local.ipynb](MyIA.AI.Notebooks/GenAI/Audio/01-Foundation/01-4-Whisper-Local.ipynb) | Whisper Local - Transcription GPU avec… | Python 3 | DEMO | BETA | 45min | po-2025 | | 5 | [01-5-Kokoro-TTS-Local.ipynb](MyIA.AI.Notebooks/GenAI/Audio/01-Foundation/01-5-Kokoro-TTS-Local.ipynb) | Kokoro TTS Local - Synthese Vocale Legere | Python 3 | DEMO | BETA | 45min | po-2025 | @@ -157,26 +158,27 @@ Total notebooks: 1312 | 4 | [04_coverage_matrix.ipynb](MyIA.AI.Notebooks/GenAI/FallacyDetection/04_coverage_matrix.ipynb) | 04 — Matrice de couverture cross-notebooks | Python 3 | READY | BETA | 15min | po-2025 | | 5 | [05_dataset_builder.ipynb](MyIA.AI.Notebooks/GenAI/FallacyDetection/05_dataset_builder.ipynb) | 05 — Constructeur du dataset de Phase 2 : produit… | Python 3 | READY | BETA | 30min | po-2025 | -#### FineTuning (10) +#### FineTuning (11) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| | 1 | [FT-00a-LoRA-from-scratch-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-00a-LoRA-from-scratch-Python.ipynb) | FT-00a : LoRA from scratch — démonter l'adaptation… | Python 3 | READY | BETA | 45min | po-2025 | | 2 | [FT-00b-LoRA-Hyperparams-from-scratch-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-00b-LoRA-Hyperparams-from-scratch-Python.ipynb) | FT-00b : LoRA hyperparams from scratch — ablation… | Python 3 | DEMO | BETA | 45min | po-2025 | | 3 | [FT-00c-LoRA-SOTA-Comparison-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-00c-LoRA-SOTA-Comparison-Python.ipynb) | FT-00c : LoRA SOTA — la même adaptation, cette… | Python 3 | READY | BETA | 45min | po-2025 | -| 4 | [FT-01-Introduction-FineTuning-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-01-Introduction-FineTuning-Python.ipynb) | FT-01 : Introduction au Fine-Tuning | Python 3 | READY | BETA | 45min | po-2025 | -| 5 | [FT-02-QLoRA-Quantization-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-02-QLoRA-Quantization-Python.ipynb) | FT-02 : QLoRA — Fine-Tuning avec Quantization | Python 3 | READY | BETA | 1h | po-2025 | -| 6 | [FT-03-Supervised-FineTuning-SFT-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-03-Supervised-FineTuning-SFT-Python.ipynb) | FT-03 : Supervised Fine-Tuning (SFT) — Enseigner… | Python 3 | READY | BETA | 45min | po-2025 | -| 7 | [FT-04-RLHF-DPO-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-04-RLHF-DPO-Python.ipynb) | FT-04 : RLHF et Alignement — Préférences Humaines… | Python 3 | READY | BETA | 45min | po-2025 | -| 8 | [FT-05-ModelMerging-Routing-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-05-ModelMerging-Routing-Python.ipynb) | FT-05 : Fusion et Routage de Modèles -- Combiner… | Python 3 | READY | BETA | 45min | po-2025 | -| 9 | [FT-05-ModelMerging-Routing-Python_en.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-05-ModelMerging-Routing-Python_en.ipynb) | FT-05: Model Merging and Routing -- Combining… | Python 3 | READY | BETA | 45min | po-2025 | -| 10 | [FT-06-Vision-Language-LoRA-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-06-Vision-Language-LoRA-Python.ipynb) | FT-06 : LoRA vision-langage — fine-tune du… | Python 3 | DEMO | BETA | 45min | po-2025 | +| 4 | [FT-00d-LoRA-QLoRA-SOTA-Comparison-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-00d-LoRA-QLoRA-SOTA-Comparison-Python.ipynb) | FT-00d : LoRA + QLoRA SOTA Comparison | Python 3 | DEMO | BETA | 30min | po-2025 | +| 5 | [FT-01-Introduction-FineTuning-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-01-Introduction-FineTuning-Python.ipynb) | FT-01 : Introduction au Fine-Tuning | Python 3 | READY | BETA | 45min | po-2025 | +| 6 | [FT-02-QLoRA-Quantization-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-02-QLoRA-Quantization-Python.ipynb) | FT-02 : QLoRA — Fine-Tuning avec Quantization | Python 3 | READY | BETA | 1h | po-2025 | +| 7 | [FT-03-Supervised-FineTuning-SFT-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-03-Supervised-FineTuning-SFT-Python.ipynb) | FT-03 : Supervised Fine-Tuning (SFT) — Enseigner… | Python 3 | READY | BETA | 45min | po-2025 | +| 8 | [FT-04-RLHF-DPO-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-04-RLHF-DPO-Python.ipynb) | FT-04 : RLHF et Alignement — Préférences Humaines… | Python 3 | READY | BETA | 45min | po-2025 | +| 9 | [FT-05-ModelMerging-Routing-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-05-ModelMerging-Routing-Python.ipynb) | FT-05 : Fusion et Routage de Modèles -- Combiner… | Python 3 | READY | BETA | 45min | po-2025 | +| 10 | [FT-05-ModelMerging-Routing-Python_en.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-05-ModelMerging-Routing-Python_en.ipynb) | FT-05: Model Merging and Routing -- Combining… | Python 3 | READY | BETA | 45min | po-2025 | +| 11 | [FT-06-Vision-Language-LoRA-Python.ipynb](MyIA.AI.Notebooks/GenAI/FineTuning/FT-06-Vision-Language-LoRA-Python.ipynb) | FT-06 : LoRA vision-langage — fine-tune du… | Python 3 | DEMO | BETA | 45min | po-2025 | #### Image (21) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| -| 1 | [01-1-OpenAI-DALL-E-3.ipynb](MyIA.AI.Notebooks/GenAI/Image/01-Foundation/01-1-OpenAI-DALL-E-3.ipynb) | OpenAI DALL-E 3 - Generation d'Images | Python 3 | DEMO | BETA | 30min | po-2025 | +| 1 | [01-1-OpenAI-DALL-E-3.ipynb](MyIA.AI.Notebooks/GenAI/Image/01-Foundation/01-1-OpenAI-DALL-E-3.ipynb) | OpenAI DALL-E 3 - Generation d'Images | Python 3 | DEMO | BETA | 45min | po-2025 | | 2 | [01-2-GPT-5-Image-Generation.ipynb](MyIA.AI.Notebooks/GenAI/Image/01-Foundation/01-2-GPT-5-Image-Generation.ipynb) | GPT-5 Multimodal - Analyse et Génération d'Images | Python 3 | DEMO | BETA | 30min | po-2025 | | 3 | [01-3-Basic-Image-Operations.ipynb](MyIA.AI.Notebooks/GenAI/Image/01-Foundation/01-3-Basic-Image-Operations.ipynb) | Opérations de Base sur les Images | Python 3 | DEMO | BETA | 45min | po-2025 | | 4 | [01-4-Forge-SD-XL-Turbo.ipynb](MyIA.AI.Notebooks/GenAI/Image/01-Foundation/01-4-Forge-SD-XL-Turbo.ipynb) | Stable Diffusion Forge - SD XL Turbo | Python 3 | DEMO | BETA | 30min | po-2025 | @@ -273,8 +275,8 @@ Total notebooks: 1312 | 16 | [PT_13_dapo_drgrpo_corrections.ipynb](MyIA.AI.Notebooks/GenAI/PostTraining/PT_13_dapo_drgrpo_corrections.ipynb) | PT-13 — Les trois biais du loss GRPO et leurs… | Coursia ML Training | READY | ALPHA | 45min | po-2025 | | 17 | [PT_14_neural_thermodynamic_laws.ipynb](MyIA.AI.Notebooks/GenAI/PostTraining/PT_14_neural_thermodynamic_laws.ipynb) | PT-14 — Lois thermodynamiques de l'entraînement :… | Coursia ML Training | READY | BETA | 30min | po-2025 | | 18 | [PT_15_controle_interpretabilite.ipynb](MyIA.AI.Notebooks/GenAI/PostTraining/PT_15_controle_interpretabilite.ipynb) | PT-15 — Contrôle par interprétabilité : refusal… | Python 3 | READY | BETA | 45min | po-2025 | -| 19 | [PT_16_vericoding_formal_verification.ipynb](MyIA.AI.Notebooks/GenAI/PostTraining/PT_16_vericoding_formal_verification.ipynb) | PT-16 — Vericoding : la preuve formelle comme… | Python 3 | READY | ALPHA | 30min | po-2025 | -| 20 | [PT_17_laya_proper_rewards_toy.ipynb](MyIA.AI.Notebooks/GenAI/PostTraining/PT_17_laya_proper_rewards_toy.ipynb) | PT-17 — laya : la règle de score propre comme… | Python 3 (coursia-ml-training) | READY | BETA | 30min | po-2025 | +| 19 | [PT_16_vericoding_formal_verification.ipynb](MyIA.AI.Notebooks/GenAI/PostTraining/PT_16_vericoding_formal_verification.ipynb) | PT-16 — Vericoding : la preuve formelle comme… | Python 3 | READY | BETA | 30min | po-2025 | +| 20 | [PT_17_laya_proper_rewards_toy.ipynb](MyIA.AI.Notebooks/GenAI/PostTraining/PT_17_laya_proper_rewards_toy.ipynb) | PT-17 — laya : la règle de score propre comme… | Python 3 (coursia-ml-training) | READY | BETA | 45min | po-2025 | #### RAG-et-Memoire-Semantique (10) @@ -291,7 +293,7 @@ Total notebooks: 1312 | 9 | [08-KernelMemory-Hybrid-Search.ipynb](MyIA.AI.Notebooks/GenAI/RAG-et-Memoire-Semantique/08-KernelMemory-Hybrid-Search.ipynb) | RAG 08 — Kernel Memory et la recherche hybride :… | Python 3 | READY | BETA | 45min | po-2025 | | 10 | [09-KernelMemory-Multimodal.ipynb](MyIA.AI.Notebooks/GenAI/RAG-et-Memoire-Semantique/09-KernelMemory-Multimodal.ipynb) | RAG 09 — Au-delà du texte : le plafond multimodal… | Python 3 | READY | BETA | 45min | po-2025 | -#### Security (5) +#### Security (6) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -300,8 +302,9 @@ Total notebooks: 1312 | 3 | [Oversight-Scaling-Laws-Nim.ipynb](MyIA.AI.Notebooks/GenAI/Security/Oversight/Oversight-Scaling-Laws-Nim.ipynb) | Oversight — Scaling Laws sur le jeu de Nim (R12,… | Python 3 | READY | BETA | 30min | po-2025 | | 4 | [Oversight-Scaling-Laws-Statistics.ipynb](MyIA.AI.Notebooks/GenAI/Security/Oversight/Oversight-Scaling-Laws-Statistics.ipynb) | Oversight-Scaling-Laws-Statistics | Python 3 | READY | BETA | 30min | po-2025 | | 5 | [Oversight-Scaling-Laws-Wargames.ipynb](MyIA.AI.Notebooks/GenAI/Security/Oversight/Oversight-Scaling-Laws-Wargames.ipynb) | Oversight-Scaling-Laws-Wargames | Python 3 | READY | BETA | 30min | po-2025 | +| 6 | [Tooling-MCP-Attack-Surface.ipynb](MyIA.AI.Notebooks/GenAI/Security/Tooling/Tooling-MCP-Attack-Surface.ipynb) | Surface d'attaque des outils MCP — le piège de la… | Python 3 | READY | BETA | 30min | po-2025 | -#### SemanticKernel (20) +#### SemanticKernel (21) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -317,62 +320,70 @@ Total notebooks: 1312 | 10 | [10-SemanticKernel-NotebookMaker.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/10-SemanticKernel-NotebookMaker.ipynb) | SK-10-NotebookMaker : Système Multi-Agents pour… | Python 3 | DEMO | BETA | 30min | po-2025 | | 11 | [10a-SemanticKernel-NotebookMaker-batch.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/10a-SemanticKernel-NotebookMaker-batch.ipynb) | Conception Automatique de Notebook par Agents IA | Python 3 | DEMO | DRAFT | 45min | po-2025 | | 12 | [10b-SemanticKernel-NotebookMaker-batch-parameterized.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/10b-SemanticKernel-NotebookMaker-batch-parameterized.ipynb) | Conception Automatique de Notebook par Agents IA | Python 3 | DEMO | BETA | 45min | po-2025 | -| 13 | [Créateur de mail personnalisé.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/Cr%C3%A9ateur%20de%20mail%20personnalis%C3%A9.ipynb) | Projet Createur de Mail personnalise | Python 3 | DEMO | BETA | 30min | po-2025 | -| 14 | [Notebook-Generated.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/Notebook-Generated.ipynb) | Notebook de travail — Titanic: exploration,… | Python 3 | READY | BETA | 15min | po-2025 | -| 15 | [Notebook-Template.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/Notebook-Template.ipynb) | Notebook de travail | Python 3 | BROKEN | TEMPLATE | 15min | po-2025 | -| 16 | [Semantic-kernel-AutoInteractive.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/Semantic-kernel-AutoInteractive.ipynb) | Notebook de conception de Notebook | .NET (C#) | DEMO | BETA | 45min | po-2025 | -| 17 | [Workbook-Template-Python.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/Workbook-Template-Python.ipynb) | Notebook de travail | .NET (C#) | READY | TEMPLATE | 30min | po-2025 | -| 18 | [Workbook-Template.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/Workbook-Template.ipynb) | Notebook de travail | .NET (C#) | BROKEN | TEMPLATE | 30min | po-2025 | -| 19 | [fort-boyard-csharp.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/fort-boyard-csharp.ipynb) | Jeu de devinette : Père Fouras vs Laurent Jalabert | .NET (C#) | DEMO | DRAFT | 30min | po-2025 | -| 20 | [fort-boyard-python.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/fort-boyard-python.ipynb) | Jeu de devinette : Père Fouras vs Laurent Jalabert | Python 3 | DEMO | BETA | 30min | po-2025 | - -#### Texte (34) +| 13 | [11-SemanticKernel-A2A.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/11-SemanticKernel-A2A.ipynb) | SK-11-A2A : le protocole Agent2Agent à côté de MCP | Python 3 | READY | BETA | 30min | po-2025 | +| 14 | [Créateur de mail personnalisé.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/Cr%C3%A9ateur%20de%20mail%20personnalis%C3%A9.ipynb) | Projet Createur de Mail personnalise | Python 3 | DEMO | BETA | 30min | po-2025 | +| 15 | [Notebook-Generated.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/Notebook-Generated.ipynb) | Notebook de travail — Titanic: exploration,… | Python 3 | READY | BETA | 15min | po-2025 | +| 16 | [Notebook-Template.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/Notebook-Template.ipynb) | Notebook de travail | Python 3 | BROKEN | TEMPLATE | 15min | po-2025 | +| 17 | [Semantic-kernel-AutoInteractive.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/Semantic-kernel-AutoInteractive.ipynb) | Notebook de conception de Notebook | .NET (C#) | DEMO | BETA | 45min | po-2025 | +| 18 | [Workbook-Template-Python.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/Workbook-Template-Python.ipynb) | Notebook de travail | .NET (C#) | READY | TEMPLATE | 30min | po-2025 | +| 19 | [Workbook-Template.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/Workbook-Template.ipynb) | Notebook de travail | .NET (C#) | BROKEN | TEMPLATE | 30min | po-2025 | +| 20 | [fort-boyard-csharp.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/fort-boyard-csharp.ipynb) | Jeu de devinette : Père Fouras vs Laurent Jalabert | .NET (C#) | DEMO | DRAFT | 30min | po-2025 | +| 21 | [fort-boyard-python.ipynb](MyIA.AI.Notebooks/GenAI/SemanticKernel/fort-boyard-python.ipynb) | Jeu de devinette : Père Fouras vs Laurent Jalabert | Python 3 | DEMO | BETA | 30min | po-2025 | + +#### Texte (41) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| | 1 | [01_OpenAI_Intro.ipynb](MyIA.AI.Notebooks/GenAI/Texte/01_OpenAI_Intro.ipynb) | 1. Introduction a l'IA generative avec l'API… | Python 3 | DEMO | BETA | 30min | po-2025 | | 2 | [02_PromptEngineering.ipynb](MyIA.AI.Notebooks/GenAI/Texte/02_PromptEngineering.ipynb) | 2. Prompt Engineering : Techniques Avancées | Python 3 | DEMO | ALPHA | 45min | po-2025 | -| 3 | [03_Structured_Outputs.ipynb](MyIA.AI.Notebooks/GenAI/Texte/03_Structured_Outputs.ipynb) | 3. Structured Outputs : Sorties JSON Garanties | Python 3 | DEMO | BETA | 30min | po-2025 | -| 4 | [04_Function_Calling.ipynb](MyIA.AI.Notebooks/GenAI/Texte/04_Function_Calling.ipynb) | Function Calling : Connecter les LLMs au Monde… | Python 3 | DEMO | BETA | 45min | po-2025 | -| 5 | [05_RAG_Modern.ipynb](MyIA.AI.Notebooks/GenAI/Texte/05_RAG_Modern.ipynb) | 5. RAG Modern - Retrieval Augmented Generation | Python 3 | DEMO | BETA | 45min | po-2025 | -| 6 | [06_PDF_Web_Search.ipynb](MyIA.AI.Notebooks/GenAI/Texte/06_PDF_Web_Search.ipynb) | PDF et Web Search : Sources Documentaires avec… | Python 3 | DEMO | BETA | 30min | po-2025 | -| 7 | [07_Code_Interpreter.ipynb](MyIA.AI.Notebooks/GenAI/Texte/07_Code_Interpreter.ipynb) | Code Interpreter : Exécution de Code avec OpenAI | Python 3 | DEMO | BETA | 30min | po-2025 | -| 8 | [08_Reasoning_Models.ipynb](MyIA.AI.Notebooks/GenAI/Texte/08_Reasoning_Models.ipynb) | 8. Reasoning Models | Python 3 | DEMO | BETA | 30min | po-2025 | -| 9 | [09_Production_Patterns.ipynb](MyIA.AI.Notebooks/GenAI/Texte/09_Production_Patterns.ipynb) | 9. Production Patterns | Python 3 | DEMO | BETA | 30min | po-2025 | -| 10 | [09b_Prompt_Security_RedTeam.ipynb](MyIA.AI.Notebooks/GenAI/Texte/09b_Prompt_Security_RedTeam.ipynb) | 9b. Prompt Security & Red-Teaming sur notre stack… | Python 3 | DEMO | BETA | 30min | po-2025 | -| 11 | [10_LocalLlama.ipynb](MyIA.AI.Notebooks/GenAI/Texte/10_LocalLlama.ipynb) | 10. Hébergement Local de Modèles Génératifs | Python 3 | DEMO | BETA | 45min | po-2025 | -| 12 | [10b_Inference_Mechanics.ipynb](MyIA.AI.Notebooks/GenAI/Texte/10b_Inference_Mechanics.ipynb) | 10b. Mécanique d'inférence LLM : construire et… | Python 3 | READY | BETA | 30min | po-2025 | -| 13 | [10c_Long_Context_Strategies.ipynb](MyIA.AI.Notebooks/GenAI/Texte/10c_Long_Context_Strategies.ipynb) | 10c. Stratégies pour contextes longs — budget de… | Python 3 | READY | BETA | 45min | po-2025 | -| 14 | [10d_TensorSharp_DotNet_Inference.ipynb](MyIA.AI.Notebooks/GenAI/Texte/10d_TensorSharp_DotNet_Inference.ipynb) | 10d. TensorSharp : pilote d'inférence LLM native… | .NET (C#) | READY | BETA | 45min | po-2025 | -| 15 | [10e_LLamaSharp_DotNet_BakeOff.ipynb](MyIA.AI.Notebooks/GenAI/Texte/10e_LLamaSharp_DotNet_BakeOff.ipynb) | 10e. LLamaSharp : bake-off binding .NET de… | Python 3 | READY | BETA | 45min | po-2025 | -| 16 | [10f_ORTGenAI_DotNet_BakeOff.ipynb](MyIA.AI.Notebooks/GenAI/Texte/10f_ORTGenAI_DotNet_BakeOff.ipynb) | 10f. ONNX Runtime GenAI : jambe finale du bake-off… | .NET (C#) | READY | BETA | 45min | po-2025 | -| 17 | [11_Quantization.ipynb](MyIA.AI.Notebooks/GenAI/Texte/11_Quantization.ipynb) | 11. Quantization | Python 3 | DEMO | BETA | 45min | po-2025 | -| 18 | [12_Test_Time_Scaling.ipynb](MyIA.AI.Notebooks/GenAI/Texte/12_Test_Time_Scaling.ipynb) | 12. Test Time Scaling | Python 3 | DEMO | BETA | 45min | po-2025 | -| 19 | [13_Agentic_Orchestration.ipynb](MyIA.AI.Notebooks/GenAI/Texte/13_Agentic_Orchestration.ipynb) | 13. Orchestration agentique du test-time scaling | Python 3 | READY | BETA | 45min | po-2025 | -| 20 | [13b_Agent_Evaluation.ipynb](MyIA.AI.Notebooks/GenAI/Texte/13b_Agent_Evaluation.ipynb) | 13b — Évaluation d'agents : succès, coût, ablation… | Python 3 (coursia2) | READY | BETA | 30min | po-2025 | -| 21 | [14_Persistent_Memory.ipynb](MyIA.AI.Notebooks/GenAI/Texte/14_Persistent_Memory.ipynb) | 14. Memoire persistante pour le test-time scaling | Python 3 | READY | BETA | 30min | po-2025 | -| 22 | [15_Tree_of_Thoughts_Search.ipynb](MyIA.AI.Notebooks/GenAI/Texte/15_Tree_of_Thoughts_Search.ipynb) | 15. Tree-of-Thoughts sur de vrais problemes de… | Python 3 | READY | BETA | 30min | po-2025 | -| 23 | [16_Scaling_Test_Time_Compute.ipynb](MyIA.AI.Notebooks/GenAI/Texte/16_Scaling_Test_Time_Compute.ipynb) | 16. Scaling du test-time compute (Snell 2024) | Python 3 | READY | BETA | 30min | po-2025 | -| 24 | [17_Native_Reasoning_vs_Scaling.ipynb](MyIA.AI.Notebooks/GenAI/Texte/17_Native_Reasoning_vs_Scaling.ipynb) | 17. Modèles a raisonnement natif vs scaling du… | Python 3 | READY | BETA | 30min | po-2025 | -| 25 | [18_Semantic_Kernel_Plugins.ipynb](MyIA.AI.Notebooks/GenAI/Texte/18_Semantic_Kernel_Plugins.ipynb) | 18. Plugins Semantic Kernel pour le test-time… | Python 3 | READY | BETA | 30min | po-2025 | -| 26 | [19_OWUI_Orchestration.ipynb](MyIA.AI.Notebooks/GenAI/Texte/19_OWUI_Orchestration.ipynb) | 19. Orchestration et tâches planifiées avec Open… | Python 3 | READY | BETA | 30min | po-2025 | -| 27 | [20_OWUI_Native_API.ipynb](MyIA.AI.Notebooks/GenAI/Texte/20_OWUI_Native_API.ipynb) | 20. OWUI Native API v0.9.6 — introspection REST et… | Python 3 | READY | BETA | 30min | po-2025 | -| 28 | [21_LoRA_FineTuning.ipynb](MyIA.AI.Notebooks/GenAI/Texte/21_LoRA_FineTuning.ipynb) | 21. Fine-tuning LoRA / QLoRA — Adapter un LLM sans… | Python (coursia-ml-training) | READY | DRAFT | 45min | po-2025 | -| 29 | [22_Evaluating_Generated_Text.ipynb](MyIA.AI.Notebooks/GenAI/Texte/22_Evaluating_Generated_Text.ipynb) | 22 — Évaluer les sorties générées : BLEU, ROUGE,… | Python 3 | READY | BETA | 45min | po-2025 | -| 30 | [22b_Profil_Cognitif_CHC.ipynb](MyIA.AI.Notebooks/GenAI/Texte/22b_Profil_Cognitif_CHC.ipynb) | 22b — Profil cognitif d'un LLM : batterie CHC,… | Python (coursia-ml-training) | READY | BETA | 45min | po-2025 | -| 31 | [TV-00a-RoPE-from-scratch.ipynb](MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-00a-RoPE-from-scratch.ipynb) | TV-00a — RoPE from scratch : coder la position par… | Python 3 | READY | BETA | 30min | po-2025 | -| 32 | [TV-00b-Attention-Variants-from-scratch.ipynb](MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-00b-Attention-Variants-from-scratch.ipynb) | TV-00b — Variantes d'attention : MHA, MQA, GQA,… | Python 3 | DEMO | BETA | 45min | po-2025 | -| 33 | [TV-01-Attention-Variants-SOTA.ipynb](MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-01-Attention-Variants-SOTA.ipynb) | TV-01 — La boîte ouverte côté industrie :… | Python 3 | DEMO | BETA | 45min | po-2025 | -| 34 | [TV-02-MoE-SOTA.ipynb](MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-02-MoE-SOTA.ipynb) | TV-02 — MoE SOTA : le routage réel d'OLMoE-1B-7B | Python 3 | DEMO | BETA | 45min | po-2025 | +| 3 | [03_Structured_Outputs.ipynb](MyIA.AI.Notebooks/GenAI/Texte/03_Structured_Outputs.ipynb) | 3. Structured Outputs : Sorties JSON Garanties | base | DEMO | BETA | 45min | po-2025 | +| 4 | [03b_Typed_Decisions_System1.ipynb](MyIA.AI.Notebooks/GenAI/Texte/03b_Typed_Decisions_System1.ipynb) | 3b. Décisions typées « système 1 » : décider sans… | Python 3 | DEMO | BETA | 45min | po-2025 | +| 5 | [03c_Constrained_Decoding_Python.ipynb](MyIA.AI.Notebooks/GenAI/Texte/03c_Constrained_Decoding_Python.ipynb) | 3c. Décodage contraint au niveau du token | Python 3 | READY | BETA | 30min | po-2025 | +| 6 | [04_Function_Calling.ipynb](MyIA.AI.Notebooks/GenAI/Texte/04_Function_Calling.ipynb) | Function Calling : Connecter les LLMs au Monde… | Python 3 | DEMO | BETA | 45min | po-2025 | +| 7 | [05_RAG_Modern.ipynb](MyIA.AI.Notebooks/GenAI/Texte/05_RAG_Modern.ipynb) | 5. RAG Modern - Retrieval Augmented Generation | Python 3 | DEMO | BETA | 45min | po-2025 | +| 8 | [06_PDF_Web_Search.ipynb](MyIA.AI.Notebooks/GenAI/Texte/06_PDF_Web_Search.ipynb) | PDF et Web Search : Sources Documentaires avec… | Python 3 | DEMO | BETA | 45min | po-2025 | +| 9 | [07_Code_Interpreter.ipynb](MyIA.AI.Notebooks/GenAI/Texte/07_Code_Interpreter.ipynb) | Code Interpreter : Exécution de Code avec OpenAI | Python 3 | DEMO | BETA | 30min | po-2025 | +| 10 | [08_Reasoning_Models.ipynb](MyIA.AI.Notebooks/GenAI/Texte/08_Reasoning_Models.ipynb) | 8. Reasoning Models | Python 3 | DEMO | BETA | 30min | po-2025 | +| 11 | [09_Production_Patterns.ipynb](MyIA.AI.Notebooks/GenAI/Texte/09_Production_Patterns.ipynb) | 9. Production Patterns | Python 3 | DEMO | BETA | 30min | po-2025 | +| 12 | [09b_Prompt_Security_RedTeam.ipynb](MyIA.AI.Notebooks/GenAI/Texte/09b_Prompt_Security_RedTeam.ipynb) | 9b. Prompt Security & Red-Teaming sur notre stack… | Python 3 | DEMO | BETA | 30min | po-2025 | +| 13 | [09c_Production_Routage_Repli.ipynb](MyIA.AI.Notebooks/GenAI/Texte/09c_Production_Routage_Repli.ipynb) | 9c. Routage et Repli : choisir le bon modèle, au… | Python 3 | DEMO | BETA | 45min | po-2025 | +| 14 | [09d_Production_Caches.ipynb](MyIA.AI.Notebooks/GenAI/Texte/09d_Production_Caches.ipynb) | 9d. Production Caches : payer une fois, servir… | Python 3 | READY | BETA | 30min | po-2025 | +| 15 | [09e_Production_Exploitation.ipynb](MyIA.AI.Notebooks/GenAI/Texte/09e_Production_Exploitation.ipynb) | 9e — Production : l'exploitation (coût, budget,… | Python 3 | READY | DRAFT | 30min | po-2025 | +| 16 | [10_LocalLlama.ipynb](MyIA.AI.Notebooks/GenAI/Texte/10_LocalLlama.ipynb) | 10. Hébergement Local de Modèles Génératifs | Python 3 | DEMO | BETA | 45min | po-2025 | +| 17 | [10b_Inference_Mechanics.ipynb](MyIA.AI.Notebooks/GenAI/Texte/10b_Inference_Mechanics.ipynb) | 10b. Mécanique d'inférence LLM : construire et… | Python 3 | READY | BETA | 30min | po-2025 | +| 18 | [10c_Long_Context_Strategies.ipynb](MyIA.AI.Notebooks/GenAI/Texte/10c_Long_Context_Strategies.ipynb) | 10c. Stratégies pour contextes longs — budget de… | Python 3 | READY | BETA | 45min | po-2025 | +| 19 | [10d_TensorSharp_DotNet_Inference.ipynb](MyIA.AI.Notebooks/GenAI/Texte/10d_TensorSharp_DotNet_Inference.ipynb) | 10d. TensorSharp : pilote d'inférence LLM native… | .NET (C#) | READY | BETA | 45min | po-2025 | +| 20 | [10e_LLamaSharp_DotNet_BakeOff.ipynb](MyIA.AI.Notebooks/GenAI/Texte/10e_LLamaSharp_DotNet_BakeOff.ipynb) | 10e. LLamaSharp : bake-off binding .NET de… | Python 3 | READY | BETA | 45min | po-2025 | +| 21 | [10f_ORTGenAI_DotNet_BakeOff.ipynb](MyIA.AI.Notebooks/GenAI/Texte/10f_ORTGenAI_DotNet_BakeOff.ipynb) | 10f. ONNX Runtime GenAI : jambe finale du bake-off… | .NET (C#) | READY | BETA | 45min | po-2025 | +| 22 | [11_Quantization.ipynb](MyIA.AI.Notebooks/GenAI/Texte/11_Quantization.ipynb) | 11. Quantization | Python 3 | DEMO | BETA | 45min | po-2025 | +| 23 | [12_Test_Time_Scaling.ipynb](MyIA.AI.Notebooks/GenAI/Texte/12_Test_Time_Scaling.ipynb) | 12. Test Time Scaling | Python 3 | DEMO | BETA | 45min | po-2025 | +| 24 | [13_Agentic_Orchestration.ipynb](MyIA.AI.Notebooks/GenAI/Texte/13_Agentic_Orchestration.ipynb) | 13. Orchestration agentique du test-time scaling | Python 3 | READY | BETA | 45min | po-2025 | +| 25 | [13b_Agent_Evaluation.ipynb](MyIA.AI.Notebooks/GenAI/Texte/13b_Agent_Evaluation.ipynb) | 13b — Évaluation d'agents : succès, coût, ablation… | Python 3 (coursia2) | READY | BETA | 30min | po-2025 | +| 26 | [14_Persistent_Memory.ipynb](MyIA.AI.Notebooks/GenAI/Texte/14_Persistent_Memory.ipynb) | 14. Memoire persistante pour le test-time scaling | Python 3 | READY | BETA | 30min | po-2025 | +| 27 | [14b_Paginated_Memory-Python.ipynb](MyIA.AI.Notebooks/GenAI/Texte/14b_Paginated_Memory-Python.ipynb) | 14b. Memoire paginee d'agent -- fenetre glissante,… | Python 3 | READY | BETA | 30min | po-2025 | +| 28 | [15_Tree_of_Thoughts_Search.ipynb](MyIA.AI.Notebooks/GenAI/Texte/15_Tree_of_Thoughts_Search.ipynb) | 15. Tree-of-Thoughts sur de vrais problemes de… | Python 3 | READY | BETA | 30min | po-2025 | +| 29 | [16_Scaling_Test_Time_Compute.ipynb](MyIA.AI.Notebooks/GenAI/Texte/16_Scaling_Test_Time_Compute.ipynb) | 16. Scaling du test-time compute (Snell 2024) | Python 3 | READY | BETA | 30min | po-2025 | +| 30 | [17_Native_Reasoning_vs_Scaling.ipynb](MyIA.AI.Notebooks/GenAI/Texte/17_Native_Reasoning_vs_Scaling.ipynb) | 17. Modèles a raisonnement natif vs scaling du… | Python 3 | READY | BETA | 30min | po-2025 | +| 31 | [18_Semantic_Kernel_Plugins.ipynb](MyIA.AI.Notebooks/GenAI/Texte/18_Semantic_Kernel_Plugins.ipynb) | 18. Plugins Semantic Kernel pour le test-time… | Python 3 | READY | BETA | 30min | po-2025 | +| 32 | [19_OWUI_Orchestration.ipynb](MyIA.AI.Notebooks/GenAI/Texte/19_OWUI_Orchestration.ipynb) | 19. Orchestration et tâches planifiées avec Open… | Python 3 | READY | BETA | 30min | po-2025 | +| 33 | [20_OWUI_Native_API.ipynb](MyIA.AI.Notebooks/GenAI/Texte/20_OWUI_Native_API.ipynb) | 20. OWUI Native API v0.9.6 — introspection REST et… | Python 3 | READY | BETA | 30min | po-2025 | +| 34 | [21_LoRA_FineTuning.ipynb](MyIA.AI.Notebooks/GenAI/Texte/21_LoRA_FineTuning.ipynb) | 21. Fine-tuning LoRA / QLoRA — Adapter un LLM sans… | Python (coursia-ml-training) | READY | DRAFT | 45min | po-2025 | +| 35 | [22_Evaluating_Generated_Text.ipynb](MyIA.AI.Notebooks/GenAI/Texte/22_Evaluating_Generated_Text.ipynb) | 22 — Évaluer les sorties générées : BLEU, ROUGE,… | Python 3 | READY | BETA | 45min | po-2025 | +| 36 | [22b_Profil_Cognitif_CHC.ipynb](MyIA.AI.Notebooks/GenAI/Texte/22b_Profil_Cognitif_CHC.ipynb) | 22b — Profil cognitif d'un LLM : batterie CHC,… | Python (coursia-ml-training) | READY | BETA | 45min | po-2025 | +| 37 | [TV-00a-RoPE-from-scratch.ipynb](MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-00a-RoPE-from-scratch.ipynb) | TV-00a — RoPE from scratch : coder la position par… | Python 3 | READY | BETA | 30min | po-2025 | +| 38 | [TV-00b-Attention-Variants-from-scratch.ipynb](MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-00b-Attention-Variants-from-scratch.ipynb) | TV-00b — Variantes d'attention : MHA, MQA, GQA,… | Python 3 | DEMO | BETA | 45min | po-2025 | +| 39 | [TV-01-Attention-Variants-SOTA.ipynb](MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-01-Attention-Variants-SOTA.ipynb) | TV-01 — La boîte ouverte côté industrie :… | Python 3 | DEMO | BETA | 45min | po-2025 | +| 40 | [TV-02-MoE-SOTA.ipynb](MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-02-MoE-SOTA.ipynb) | TV-02 — MoE SOTA : le routage réel d'OLMoE-1B-7B | Python 3 | DEMO | BETA | 45min | po-2025 | +| 41 | [TV-03-Internalisation-CoT.ipynb](MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-03-Internalisation-CoT.ipynb) | TV-03 -- Internalisation du raisonnement (CoT ->… | Python 3 | READY | BETA | 30min | po-2025 | #### Vibe-Coding (8) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| -| 1 | [01-Claude-CLI-Bases.ipynb](MyIA.AI.Notebooks/GenAI/Vibe-Coding/Claude-Code/notebooks/01-Claude-CLI-Bases.ipynb) | Claude CLI - Les Bases | Python 3 | READY | BETA | 45min | po-2025 | +| 1 | [01-Claude-CLI-Bases.ipynb](MyIA.AI.Notebooks/GenAI/Vibe-Coding/Claude-Code/notebooks/01-Claude-CLI-Bases.ipynb) | Claude CLI - Les Bases | base | READY | BETA | 45min | po-2025 | | 2 | [02-Claude-CLI-Sessions.ipynb](MyIA.AI.Notebooks/GenAI/Vibe-Coding/Claude-Code/notebooks/02-Claude-CLI-Sessions.ipynb) | Claude CLI - Gestion des Sessions | Python 3 | READY | BETA | 45min | po-2025 | | 3 | [03-Claude-CLI-References.ipynb](MyIA.AI.Notebooks/GenAI/Vibe-Coding/Claude-Code/notebooks/03-Claude-CLI-References.ipynb) | Claude CLI - References et Contexte | Python 3 | READY | BETA | 45min | po-2025 | -| 4 | [04-Claude-CLI-Agents.ipynb](MyIA.AI.Notebooks/GenAI/Vibe-Coding/Claude-Code/notebooks/04-Claude-CLI-Agents.ipynb) | Claude CLI - Agents et Subagents | Python 3 | READY | BETA | 30min | po-2025 | +| 4 | [04-Claude-CLI-Agents.ipynb](MyIA.AI.Notebooks/GenAI/Vibe-Coding/Claude-Code/notebooks/04-Claude-CLI-Agents.ipynb) | Claude CLI - Agents et Subagents | Python 3 | READY | BETA | 45min | po-2025 | | 5 | [05-Claude-CLI-Automatisation.ipynb](MyIA.AI.Notebooks/GenAI/Vibe-Coding/Claude-Code/notebooks/05-Claude-CLI-Automatisation.ipynb) | Claude CLI - Automatisation Avancee | Python 3 | READY | BETA | 45min | po-2025 | | 6 | [01-claude-code-via-claudish.ipynb](MyIA.AI.Notebooks/GenAI/Vibe-Coding/Claudish/notebooks/01-claude-code-via-claudish.ipynb) | Claude Code via Claudish | Python 3 | READY | BETA | 15min | po-2025 | | 7 | [CSharpRepl-Live-Patching.ipynb](MyIA.AI.Notebooks/GenAI/Vibe-Coding/docs/CSharpRepl-Live-Patching.ipynb) | CSharpRepl attache a un process .NET vivant | .NET (C#) | READY | ALPHA | 1h | po-2025 | @@ -382,7 +393,7 @@ Total notebooks: 1312 | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| -| 1 | [01-1-Video-Operations-Basics.ipynb](MyIA.AI.Notebooks/GenAI/Video/01-Foundation/01-1-Video-Operations-Basics.ipynb) | Opérations de Base sur les Videos | Python 3 | DEMO | BETA | 45min | po-2025 | +| 1 | [01-1-Video-Operations-Basics.ipynb](MyIA.AI.Notebooks/GenAI/Video/01-Foundation/01-1-Video-Operations-Basics.ipynb) | Opérations de Base sur les Videos | Python 3 | DEMO | ALPHA | 45min | po-2025 | | 2 | [01-1b-Video-Slideshow-Bonus.ipynb](MyIA.AI.Notebooks/GenAI/Video/01-Foundation/01-1b-Video-Slideshow-Bonus.ipynb) | Bonus Slideshow Vidéo - Générateur de Slideshow… | Python 3 | READY | ALPHA | 15min | po-2025 | | 3 | [01-2-GPT-5-Video-Understanding.ipynb](MyIA.AI.Notebooks/GenAI/Video/01-Foundation/01-2-GPT-5-Video-Understanding.ipynb) | GPT-5 Video Understanding - Comprehension Video… | Python 3 | DEMO | BETA | 45min | po-2025 | | 4 | [01-3-Qwen-VL-Video-Analysis.ipynb](MyIA.AI.Notebooks/GenAI/Video/01-Foundation/01-3-Qwen-VL-Video-Analysis.ipynb) | Qwen2.5-VL Video Analysis - Comprehension Video… | Python 3 | DEMO | BETA | 45min | po-2025 | @@ -405,7 +416,7 @@ Total notebooks: 1312 | 21 | [04-5-MiniMax-H3-Cloud-Video.ipynb](MyIA.AI.Notebooks/GenAI/Video/04-Applications/04-5-MiniMax-H3-Cloud-Video.ipynb) | MiniMax H3 (Hailuo) — Génération vidéo par le… | Python 3 | DEMO | BETA | 30min | po-2025 | | 22 | [04-5b-MiniMax-video-01-v1-Cloud-Video.ipynb](MyIA.AI.Notebooks/GenAI/Video/04-Applications/04-5b-MiniMax-video-01-v1-Cloud-Video.ipynb) | MiniMax video-01 (v1) — Service cloud generation… | Python 3 | DEMO | BETA | 30min | po-2025 | -### Search (155 notebooks) — READY:155 | ALPHA:9, BETA:141, DRAFT:5 +### Search (156 notebooks) — READY:156 | ALPHA:9, BETA:141, DRAFT:6 #### Applications (59) @@ -471,6 +482,12 @@ Total notebooks: 1312 | 58 | [App-14c-ConnectFour-CSharp.ipynb](MyIA.AI.Notebooks/Search/Applications/Search/App-14c-ConnectFour-CSharp.ipynb) | App-14c (C#) : Puissance 4 -- Comparaison… | .NET (C#) | READY | BETA | 45min | po-2025 | | 59 | [App-32-Szpiro-Pasten-2026.ipynb](MyIA.AI.Notebooks/Search/Applications/Search/App-32-Szpiro-Pasten-2026.ipynb) | App-32 — Szpiro : Pasten 2026 rend N log log N… | Python 3 | READY | BETA | 15min | po-2025 | +#### Discrepancy (1) + +| # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | +|---|----------|-------|--------|--------|----------|----------|-------| +| 1 | [Discrepancy-01-BeckFiala-Lean-Python.ipynb](MyIA.AI.Notebooks/Search/Discrepancy/Discrepancy-01-BeckFiala-Lean-Python.ipynb) | Discrepancy-01 - Beck-Fiala (la noix disc <= 2k-1)… | Python 3 | READY | DRAFT | 15min | po-2025 | + #### Part1-Foundations (43) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | @@ -582,15 +599,15 @@ Total notebooks: 1312 | 34 | [MGS-30-ScatterSearch-Decomposition.ipynb](MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-vs-mealpy/MGS-30-ScatterSearch-Decomposition.ipynb) | MGS-30 : Scatter Search MGS contre son ombre — la… | .NET (C#) | READY | BETA | 45min | po-2025 | | 35 | [MGS-31-Synthese-Croisee.ipynb](MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-vs-mealpy/MGS-31-Synthese-Croisee.ipynb) | MGS-31 : Synthèse croisée MGS contre mealpy — neuf… | .NET (C#) | READY | DRAFT | 30min | po-2025 | -### ML (120 notebooks) — DEMO:16, READY:104 | ALPHA:6, BETA:110, DRAFT:4 +### ML (126 notebooks) — DEMO:18, READY:108 | ALPHA:7, BETA:114, DRAFT:5 -#### DataScienceWithAgents (97) +#### DataScienceWithAgents (103) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| | 1 | [1.2-Manipulation_de_Donnees_avec_NumPy.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.2-Manipulation_de_Donnees_avec_NumPy.ipynb) | 1.2 - Manipulation de Données avec NumPy | Python 3 | READY | BETA | 45min | po-2023 | | 2 | [1.3-Analyse_de_Donnees_avec_Pandas.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.3-Analyse_de_Donnees_avec_Pandas.ipynb) | 1.3 - Analyse de Données avec Pandas | Python 3 | READY | BETA | 30min | po-2023 | -| 3 | [2.1-Workflow-ML.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.1-Workflow-ML.ipynb) | 2.1 — Le workflow d'apprentissage automatique | Python 3 | READY | BETA | 30min | po-2023 | +| 3 | [2.1-Workflow-ML.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.1-Workflow-ML.ipynb) | 2.1 — Le workflow d'apprentissage automatique | Python 3 | READY | BETA | 45min | po-2023 | | 4 | [2.10-Optimisation-Hyperparametres.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.10-Optimisation-Hyperparametres.ipynb) | 2.10 — Optimisation d'hyperparamètres : grille,… | Python 3 | READY | BETA | 30min | po-2023 | | 5 | [2.11-Regularisation-Sparse-LASSO.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11-Regularisation-Sparse-LASSO.ipynb) | 2.11 — Régularisation sparse : LASSO (L1) vs Ridge… | Python 3 | READY | BETA | 30min | po-2023 | | 6 | [2.11b-Proximal-Operators-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11b-Proximal-Operators-From-Scratch.ipynb) | 2.11b — Operateurs proximaux : ISTA et FISTA from… | Python 3 | READY | BETA | 30min | po-2023 | @@ -602,89 +619,95 @@ Total notebooks: 1312 | 12 | [2.13-Analyse-Erreurs.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.13-Analyse-Erreurs.ipynb) | 2.13 — Analyse d'erreurs : diagnostiquer un modèle… | Python 3 | READY | BETA | 30min | po-2023 | | 13 | [2.14-Explicabilite-SHAP-LIME-Contrefactuels.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.14-Explicabilite-SHAP-LIME-Contrefactuels.ipynb) | 2.14 — Explicabilité (XAI) : SHAP, LIME et… | Python 3 | READY | BETA | 30min | po-2023 | | 14 | [2.14b-XAI-Shap-Attribution-Causal-Bridge.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.14b-XAI-Shap-Attribution-Causal-Bridge.ipynb) | 2.14b — SHAP et do-calculus : la jonction… | Python 3 (coursia-ml-training) | READY | BETA | 30min | po-2023 | -| 15 | [2.2-Descente-de-gradient.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.2-Descente-de-gradient.ipynb) | 2.2 — La descente de gradient : comment un modèle… | Python 3 | READY | BETA | 30min | po-2023 | -| 16 | [2.3-Regression-lineaire-logistique.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3-Regression-lineaire-logistique.ipynb) | 2.3 — Régression linéaire et régression logistique | Python 3 | READY | BETA | 45min | po-2023 | -| 17 | [2.3b-Naive-Bayes-Generatif.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3b-Naive-Bayes-Generatif.ipynb) | Naive Bayes génératif vs régression logistique… | Python 3 | READY | BETA | 30min | po-2023 | -| 18 | [2.3c-Regression-Grande-Dimension.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3c-Regression-Grande-Dimension.ipynb) | Régression en grande dimension — quand p >> n :… | Python 3 | READY | BETA | 30min | po-2023 | -| 19 | [2.3d-Modele-Gaussien-LDA-QDA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3d-Modele-Gaussien-LDA-QDA.ipynb) | Modèle gaussien, frontière LDA / QDA | Python 3 | READY | BETA | 30min | po-2023 | -| 20 | [2.4-Arbres-Forets-Ensembles.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.4-Arbres-Forets-Ensembles.ipynb) | 2.4 — Arbres de décision, forêts aléatoires et… | Python 3 | READY | BETA | 30min | po-2023 | -| 21 | [2.5-Biais-Variance-CV-ROC.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5-Biais-Variance-CV-ROC.ipynb) | 2.5 — Biais, variance, validation croisée et… | Python 3 | READY | BETA | 45min | po-2023 | -| 22 | [2.5b-Calibration-Probabilites.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5b-Calibration-Probabilites.ipynb) | 2.5b — Calibration des probabilités : reliability… | Python 3 | READY | BETA | 30min | po-2023 | -| 23 | [2.5c-Equite-Sous-Groupes.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5c-Equite-Sous-Groupes.ipynb) | 2.5c — Equite par sous-groupe : compromis… | Python 3 | READY | BETA | 30min | po-2023 | -| 24 | [2.6-Clustering-KMeans-PCA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.6-Clustering-KMeans-PCA.ipynb) | 2.6 — Clustering (KMeans) et réduction de… | Python 3 | READY | BETA | 45min | po-2023 | -| 25 | [2.7-Modeles-Non-Parametriques.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.7-Modeles-Non-Parametriques.ipynb) | 2.7 — Modèles non paramétriques : SVM et k plus… | Python 3 | READY | BETA | 30min | po-2023 | -| 26 | [2.7b-SMO-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.7b-SMO-From-Scratch.ipynb) | 2.7b — SMO from scratch : SVM soft-margin, boucle… | Python 3 | READY | BETA | 30min | po-2023 | -| 27 | [2.7c-SVM-SOTA-Comparison.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.7c-SVM-SOTA-Comparison.ipynb) | 2.7c — SVM SOTA : LIBSVM sous le capot de… | Python 3 | READY | BETA | 30min | po-2023 | -| 28 | [2.8-Theorie-PAC.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8-Theorie-PAC.ipynb) | 2.8 — Théorie de l'apprentissage : PAC et… | Python 3 | READY | BETA | 30min | po-2023 | -| 29 | [2.8b-Theorie-PAC-Lean.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8b-Theorie-PAC-Lean.ipynb) | 2.8b - Theorie PAC en Lean : l'arc du lake… | Lean 4 (WSL) | READY | DRAFT | 30min | po-2023 | -| 30 | [2.8c-Borne-Temoin-Concentration.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8c-Borne-Temoin-Concentration.ipynb) | 2.8c — Borne + Témoin extrémal + Concentration :… | Python (coursia-ml-training) | READY | BETA | 15min | po-2023 | -| 31 | [2.8d-Lean-Novikoff-Convergence.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8d-Lean-Novikoff-Convergence.ipynb) | Novikoff : la convergence du perceptron, démontrée… | Lean 4 (WSL) | READY | BETA | 30min | po-2023 | -| 32 | [2.9-Grokking-Generalisation.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9-Grokking-Generalisation.ipynb) | 2.9 — Grokking : la généralisation qui arrive en… | Python 3 | READY | BETA | 30min | po-2023 | -| 33 | [2.9b-GenEFT-Theorie-Effective.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9b-GenEFT-Theorie-Effective.ipynb) | 2.9b — GenEFT : une théorie effective de la… | Python 3 | READY | BETA | 30min | po-2023 | -| 34 | [2.9c-Grokking-Diagrammes-Phases.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9c-Grokking-Diagrammes-Phases.ipynb) | 2.9c — Grokking : le diagramme de phases | Python 3 | READY | BETA | 30min | po-2023 | -| 35 | [2.9d-Features-Circulaires-Helice-Nombres.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9d-Features-Circulaires-Helice-Nombres.ipynb) | 2.9d — Features circulaires et hélice des nombres | Python 3 (coursia-ml-training) | DEMO | BETA | 1h | po-2023 | -| 36 | [2.9e-MIPS-Extraction-Programme.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9e-MIPS-Extraction-Programme.ipynb) | 2.9e — MIPS : du réseau au programme | Python 3 | READY | BETA | 45min | po-2023 | -| 37 | [3.0-Theorie-Information.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.0-Theorie-Information.ipynb) | 3.0 — Théorie de l'information : entropie, KL,… | Python 3 | READY | BETA | 30min | po-2023 | -| 38 | [3.1-Retropropagation.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.1-Retropropagation.ipynb) | 3.1 — La rétropropagation : la chaîne des… | Python 3 | READY | BETA | 30min | po-2023 | -| 39 | [3.10-Modeles-Generatifs-Diffusion-SOTA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.10-Modeles-Generatifs-Diffusion-SOTA.ipynb) | 3.10 — Le pendant SOTA : la bibliothèque diffusers… | Python 3 | READY | BETA | 45min | po-2023 | -| 40 | [3.2-Optimisateurs.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.2-Optimisateurs.ipynb) | 3.2 — Les optimisateurs : de SGD à Adam, ce qui… | Python 3 | READY | BETA | 30min | po-2023 | -| 41 | [3.3-Regularisation.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.3-Regularisation.ipynb) | 3.3 — Régularisation : dropout, weight decay,… | Python 3 | READY | BETA | 30min | po-2023 | -| 42 | [3.4-Attention-Transformer-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4-Attention-Transformer-From-Scratch.ipynb) | 3.4 — Attention et Transformer from scratch :… | Python 3 (coursia2) | READY | BETA | 45min | po-2023 | -| 43 | [3.4c-MoE-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4c-MoE-from-scratch.ipynb) | 3.4c — Mixture of Experts : router les jetons,… | Python 3 (coursia-ml-training) | READY | BETA | 45min | po-2023 | -| 44 | [3.5-Phenomenes-de-Generalisation.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.5-Phenomenes-de-Generalisation.ipynb) | 3.5 — Grokking et double descente : quand la… | Python 3 | READY | BETA | 30min | po-2023 | -| 45 | [3.6-Modeles-Generatifs.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6-Modeles-Generatifs.ipynb) | 3.6 — Modèles génératifs : trois objectifs, trois… | Python 3 | READY | BETA | 30min | po-2023 | -| 46 | [3.6b-Modeles-Generatifs-PyTorch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6b-Modeles-Generatifs-PyTorch.ipynb) | 3.6b — Modèles génératifs en PyTorch : VAE, GAN et… | Python 3 | READY | BETA | 45min | po-2023 | -| 47 | [3.6c-Modeles-Generatifs-Diffusion-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6c-Modeles-Generatifs-Diffusion-from-scratch.ipynb) | 3.6c — Modèles génératifs par diffusion : DDPM… | Python 3 (ipykernel) | DEMO | DRAFT | 1h | po-2023 | -| 48 | [3.6d-Modeles-Generatifs-Score-SDE-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6d-Modeles-Generatifs-Score-SDE-from-scratch.ipynb) | 3.6d — Modèles génératifs : Score-SDE *from… | Python 3 | DEMO | BETA | 1h | po-2023 | -| 49 | [3.6e-Modeles-Generatifs-Conditionnels-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6e-Modeles-Generatifs-Conditionnels-from-scratch.ipynb) | 3.6e — Génération conditionnelle et… | Python 3 | DEMO | BETA | 45min | po-2023 | -| 50 | [3.7-Distillation-Maitre-Eleve.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.7-Distillation-Maitre-Eleve.ipynb) | 3.7 — Distillation maître-élève : quand le savoir… | coursia-ml-training | READY | BETA | 30min | po-2023 | -| 51 | [3.8-Representations-Contrastives.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.8-Representations-Contrastives.ipynb) | Représentations contrastives modernes — du… | Python 3 | READY | BETA | 30min | po-2023 | -| 52 | [3.9-Compression-Quantization-FP.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9-Compression-Quantization-FP.ipynb) | 3.9 — Quantization FP : FP32 vers FP16 et BF16… | coursia-ml-training | READY | BETA | 45min | po-2023 | -| 53 | [3.9a-Compression-Quantization-INT8.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9a-Compression-Quantization-INT8.ipynb) | 3.9a — Compression par quantification INT8 : le… | Python 3 | READY | BETA | 45min | po-2023 | -| 54 | [3.9b-Compression-Pruning-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9b-Compression-Pruning-from-scratch.ipynb) | 3.9b — Compression par élagage : le réseau amputé… | Python 3 | DEMO | BETA | 1h | po-2023 | -| 55 | [3.9c-Pruning-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9c-Pruning-From-Scratch.ipynb) | 3.9c — Pruning from scratch : magnitude,… | Python 3 | DEMO | DRAFT | 45min | po-2023 | -| 56 | [3.9d-Compression-Distillation-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9d-Compression-Distillation-from-scratch.ipynb) | 3.9d — Compression par distillation : transférer… | Python 3 (coursia-ml-training) | DEMO | BETA | 45min | po-2023 | -| 57 | [3.9e-Compression-Quantization-SOTA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9e-Compression-Quantization-SOTA.ipynb) | 3.9e — Quantification SOTA : la même INT8, par… | Python 3 | READY | BETA | 45min | po-2023 | -| 58 | [3.9f-Compression-Pruning-SOTA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9f-Compression-Pruning-SOTA.ipynb) | 3.9f — Élagage SOTA : les mêmes masques, par… | Python 3 | READY | BETA | 45min | po-2023 | -| 59 | [3.9g-Compression-Comparatif-A-vs-B.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9g-Compression-Comparatif-A-vs-B.ipynb) | 3.9g — Comparatif compression : from scratch (Bloc… | Python 3 | READY | BETA | 45min | po-2023 | -| 60 | [4.1-Conv-NumPy-Torch-Allclose.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.1-Conv-NumPy-Torch-Allclose.ipynb) | 4.1 — Le neurone convolutif from scratch : kernel… | Python 3 | READY | BETA | 30min | po-2023 | -| 61 | [4.2-ConvNet-Profonde-Residuelles.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2-ConvNet-Profonde-Residuelles.ipynb) | 4.2 — ConvNet profonde : pourquoi les résiduelles | Python 3 | READY | BETA | 45min | po-2023 | -| 62 | [4.2b-Lean-GradientFlow-Vanishing.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2b-Lean-GradientFlow-Vanishing.ipynb) | Le gradient qui s'évanouit, le gradient qui survit… | Lean 4 (WSL) | READY | BETA | 30min | po-2023 | -| 63 | [4.2c-Detection-Anchor-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2c-Detection-Anchor-From-Scratch.ipynb) | 4.2c — Détection d'objets from scratch : la grille… | Python 3 | DEMO | BETA | 45min | po-2023 | -| 64 | [4.2d-Detection-AnchorFree-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2d-Detection-AnchorFree-From-Scratch.ipynb) | 4.2d — Détection d'objets anchor-free : le… | coursia-ml-training | READY | BETA | 45min | po-2023 | -| 65 | [4.2e-Detection-FocalLoss-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2e-Detection-FocalLoss-From-Scratch.ipynb) | 4.2e — Détection d'objets from scratch : la Focal… | Python 3 | READY | BETA | 30min | po-2023 | -| 66 | [4.2f-Detection-SOTA-Torchvision.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2f-Detection-SOTA-Torchvision.ipynb) | 4.2f — Détection SOTA : fine-tuner torchvision… | Python 3 | DEMO | BETA | 45min | po-2023 | -| 67 | [4.2g-Detection-SOTA-Ultralytics.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2g-Detection-SOTA-Ultralytics.ipynb) | 4.2g — Détection SOTA : YOLO sous ultralytics, la… | Python 3 | DEMO | BETA | 45min | po-2023 | -| 68 | [4.2h-YOLOv5-Bench-Ultralytics.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2h-YOLOv5-Bench-Ultralytics.ipynb) | 4.2h — Bench yolov5nu sur le terrain du 4.2c… | Python (coursia-ml-training) | READY | BETA | 30min | po-2023 | -| 69 | [4.2i-Detection-Ultralytics-Difficult-Scenes.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2i-Detection-Ultralytics-Difficult-Scenes.ipynb) | 4.2h — Détection SOTA : YOLO sous ultralytics,… | Python 3 (ipykernel) | DEMO | BETA | 45min | po-2023 | -| 70 | [4.3-TransferLearning-ResNet.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.3-TransferLearning-ResNet.ipynb) | 4.3 — Transfer learning : réutiliser un ResNet18… | Python 3 | READY | BETA | 45min | po-2023 | -| 71 | [WS-00a-Ondelettes-1D-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00a-Ondelettes-1D-from-scratch.ipynb) | WS-00a — Ondelettes 1D *from scratch* : analyse… | Python 3 | READY | BETA | 30min | po-2023 | -| 72 | [WS-00b-Ondelettes-2D-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00b-Ondelettes-2D-from-scratch.ipynb) | WS-00b — Ondelettes 2D *from scratch* : bandes… | Python 3 | READY | BETA | 30min | po-2023 | -| 73 | [WS-00c-Scattering-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00c-Scattering-from-scratch.ipynb) | WS-00c — Scattering 2D *from scratch* : le module… | Python 3 | READY | BETA | 30min | po-2023 | -| 74 | [WS-01-Denoising-SOTA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-01-Denoising-SOTA.ipynb) | WS-01 — Débruitage d'images : du seuillage *from… | Python 3 | READY | BETA | 30min | po-2023 | -| 75 | [WS-02-Scattering-SOTA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-02-Scattering-SOTA.ipynb) | WS-02 — Scattering SOTA : kymatio contre le moteur… | Python 3 | READY | BETA | 45min | po-2023 | -| 76 | [WS-03-Synthese-Scattering-vs-ResNet.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-03-Synthese-Scattering-vs-ResNet.ipynb) | WS-03 — Synthèse : représentation construite vs… | Python 3 | READY | BETA | 30min | po-2023 | -| 77 | [Lab1-PythonForDataScience.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day1-Foundations/Labs/Lab1-PythonForDataScience.ipynb) | Lab 1 - Les Bases de la Data Science en Python | Python 3 | READY | BETA | 30min | po-2023 | -| 78 | [Lab2-RFP-Analysis.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day2-Document-Agents/Labs/Lab2-RFP-Analysis/Lab2-RFP-Analysis.ipynb) | Lab 2 - Analyser un Appel d'Offre avec l'IA | Python 3 | DEMO | BETA | 30min | po-2023 | -| 79 | [Lab3-CV-Screening.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day2-Document-Agents/Labs/Lab3-CV-Screening/Lab3-CV-Screening.ipynb) | Lab 3 - Pré-qualifier des Candidats avec l'IA | Python 3 | DEMO | BETA | 15min | po-2023 | -| 80 | [Lab4-DataWrangling.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab4-DataWrangling/Lab4-DataWrangling.ipynb) | Lab 4 - Le Nettoyage de Données avec Pandas | Python 3 | READY | BETA | 30min | po-2023 | -| 81 | [Lab5-Viz-ML.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab5-Viz-ML/Lab5-Viz-ML.ipynb) | Lab 5 - De la Visualisation au Machine Learning | Python 3 | READY | BETA | 30min | po-2023 | -| 82 | [Lab6-First-Agent.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab6-First-Agent/Lab6-First-Agent.ipynb) | Lab 6 - Anatomie de votre premier Agent d'IA | Python 3 | DEMO | BETA | 30min | po-2023 | -| 83 | [Lab7-Data-Analysis-Agent.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab7-Data-Analysis-Agent/Lab7-Data-Analysis-Agent.ipynb) | Lab 7 - Votre premier Agent Analyste de Données | Python 3 | READY | BETA | 30min | po-2023 | -| 84 | [Lab8-ADK-Introduction.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day4-Foundations/Lab8-ADK-Introduction.ipynb) | Lab 8: Introduction au Framework ADK et… | Python 3 | DEMO | BETA | 30min | po-2023 | -| 85 | [Lab9-First-ADK-Agent.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day4-Foundations/Lab9-First-ADK-Agent.ipynb) | Lab 9: Premier Agent ADK pour Data Science | Python 3 | READY | BETA | 30min | po-2023 | -| 86 | [Lab10-File-Analyzer.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab10-File-Analyzer.ipynb) | Lab 10: Data File Analyzer (DS-STAR Component) | Python 3 | READY | BETA | 30min | po-2023 | -| 87 | [Lab11-Planner-Coder-Loop.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab11-Planner-Coder-Loop.ipynb) | Lab 11: Planner-Coder-Verifier Loop (DS-STAR Core) | Python 3 | READY | ALPHA | 45min | po-2023 | -| 88 | [Lab12-DS-Star-Workshop.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12-DS-Star-Workshop.ipynb) | Lab 12: DS-STAR Workshop - Analyse Multi-Fichiers | Python 3 | READY | BETA | 45min | po-2023 | -| 89 | [Lab12b-Sequential-Orchestration.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12b-Sequential-Orchestration.ipynb) | Lab 12b : Désignation séquentielle — le contrat… | Python 3 | READY | BETA | 30min | po-2023 | -| 90 | [Lab12c-Agent-Handoff.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12c-Agent-Handoff.ipynb) | Lab 12c : Handoff entre agents — le contrat C5, le… | Python 3 | READY | BETA | 30min | po-2023 | -| 91 | [Lab12d-Token-Usage.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12d-Token-Usage.ipynb) | Lab 12d : Tracabilite de la consommation — le… | Python 3 | READY | BETA | 30min | po-2023 | -| 92 | [Lab12e-Session-Persistence.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12e-Session-Persistence.ipynb) | Lab 12e: Persistance d'etat de session - une… | Python 3 (ipykernel) | DEMO | BETA | 30min | po-2023 | -| 93 | [Lab13-Web-Search-SOTA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab13-Web-Search-SOTA.ipynb) | Lab 13: Web Search pour Modèles SOTA (MLE-STAR… | Python 3 | READY | BETA | 30min | po-2023 | -| 94 | [Lab14-Ablation-Refinement.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab14-Ablation-Refinement.ipynb) | Lab 14: Ablation et Raffinement Ciblé (MLE-STAR… | Python 3 | READY | ALPHA | 30min | po-2023 | -| 95 | [Lab15-Kaggle-Challenge.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab15-Kaggle-Challenge.ipynb) | Lab 15: Kaggle Challenge avec MLE-STAR | Python 3 | READY | BETA | 30min | po-2023 | -| 96 | [Lab16-Data-Science-Agent.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day7-Production/Lab16-Data-Science-Agent.ipynb) | Lab 16: Data Science Agent avec GCP BigQuery | Python 3 | READY | ALPHA | 30min | po-2023 | -| 97 | [Lab17-Final-Project.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day7-Production/Lab17-Final-Project.ipynb) | Lab 17: Projet Final - Pipeline DS-STAR Complet | Python 3 | READY | ALPHA | 45min | po-2023 | +| 15 | [2.15-Donnee-Comme-Responsabilite-Python.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.15-Donnee-Comme-Responsabilite-Python.ipynb) | 2.15 — La donnée comme responsabilité : inférence… | Python 3 | READY | BETA | 45min | po-2023 | +| 16 | [2.2-Descente-de-gradient.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.2-Descente-de-gradient.ipynb) | 2.2 — La descente de gradient : comment un modèle… | Python 3 | READY | BETA | 45min | po-2023 | +| 17 | [2.3-Regression-lineaire-logistique.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3-Regression-lineaire-logistique.ipynb) | 2.3 — Régression linéaire et régression logistique | Python 3 | READY | BETA | 45min | po-2023 | +| 18 | [2.3b-Naive-Bayes-Generatif.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3b-Naive-Bayes-Generatif.ipynb) | Naive Bayes génératif vs régression logistique… | Python 3 | READY | BETA | 30min | po-2023 | +| 19 | [2.3c-Regression-Grande-Dimension.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3c-Regression-Grande-Dimension.ipynb) | Régression en grande dimension — quand p >> n :… | Python 3 | READY | BETA | 30min | po-2023 | +| 20 | [2.3d-Modele-Gaussien-LDA-QDA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3d-Modele-Gaussien-LDA-QDA.ipynb) | Modèle gaussien, frontière LDA / QDA | Python 3 | READY | BETA | 30min | po-2023 | +| 21 | [2.4-Arbres-Forets-Ensembles.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.4-Arbres-Forets-Ensembles.ipynb) | 2.4 — Arbres de décision, forêts aléatoires et… | Python 3 | READY | BETA | 45min | po-2023 | +| 22 | [2.5-Biais-Variance-CV-ROC.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5-Biais-Variance-CV-ROC.ipynb) | 2.5 — Biais, variance, validation croisée et… | Python 3 | READY | BETA | 45min | po-2023 | +| 23 | [2.5b-Calibration-Probabilites.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5b-Calibration-Probabilites.ipynb) | 2.5b — Calibration des probabilités : reliability… | Python 3 | READY | BETA | 30min | po-2023 | +| 24 | [2.5c-Equite-Sous-Groupes.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5c-Equite-Sous-Groupes.ipynb) | 2.5c — Equite par sous-groupe : compromis… | Python 3 | READY | BETA | 30min | po-2023 | +| 25 | [2.5d-Derive-Distribution-Deploiement.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5d-Derive-Distribution-Deploiement.ipynb) | 2.5d — Dérive de distribution au déploiement :… | Python 3.11 (coursia-drift) | READY | ALPHA | 45min | po-2023 | +| 26 | [2.6-Clustering-KMeans-PCA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.6-Clustering-KMeans-PCA.ipynb) | 2.6 — Clustering (KMeans) et réduction de… | Python 3 | READY | BETA | 45min | po-2023 | +| 27 | [2.7-Modeles-Non-Parametriques.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.7-Modeles-Non-Parametriques.ipynb) | 2.7 — Modèles non paramétriques : SVM et k plus… | Python 3 | READY | BETA | 30min | po-2023 | +| 28 | [2.7b-SMO-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.7b-SMO-From-Scratch.ipynb) | 2.7b — SMO from scratch : SVM soft-margin, boucle… | Python 3 | READY | BETA | 30min | po-2023 | +| 29 | [2.7c-SVM-SOTA-Comparison.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.7c-SVM-SOTA-Comparison.ipynb) | 2.7c — SVM SOTA : LIBSVM sous le capot de… | Python 3 | READY | BETA | 30min | po-2023 | +| 30 | [2.8-Theorie-PAC.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8-Theorie-PAC.ipynb) | 2.8 — Théorie de l'apprentissage : PAC et… | Python 3 | READY | BETA | 30min | po-2023 | +| 31 | [2.8b-Theorie-PAC-Lean.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8b-Theorie-PAC-Lean.ipynb) | 2.8b - Theorie PAC en Lean : l'arc du lake… | Lean 4 (WSL) | READY | DRAFT | 30min | po-2023 | +| 32 | [2.8c-Borne-Temoin-Concentration.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8c-Borne-Temoin-Concentration.ipynb) | 2.8c — Borne + Témoin extrémal + Concentration :… | Python (coursia-ml-training) | READY | BETA | 15min | po-2023 | +| 33 | [2.8d-Lean-Novikoff-Convergence.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8d-Lean-Novikoff-Convergence.ipynb) | Novikoff : la convergence du perceptron, démontrée… | Lean 4 (WSL) | READY | BETA | 30min | po-2023 | +| 34 | [2.9-Grokking-Generalisation.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9-Grokking-Generalisation.ipynb) | 2.9 — Grokking : la généralisation qui arrive en… | Python 3 | READY | BETA | 30min | po-2023 | +| 35 | [2.9b-GenEFT-Theorie-Effective.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9b-GenEFT-Theorie-Effective.ipynb) | 2.9b — GenEFT : une théorie effective de la… | Python 3 | READY | BETA | 30min | po-2023 | +| 36 | [2.9c-Grokking-Diagrammes-Phases.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9c-Grokking-Diagrammes-Phases.ipynb) | 2.9c — Grokking : le diagramme de phases | Python 3 | READY | BETA | 30min | po-2023 | +| 37 | [2.9d-Features-Circulaires-Helice-Nombres.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9d-Features-Circulaires-Helice-Nombres.ipynb) | 2.9d — Features circulaires et hélice des nombres | Python 3 (coursia-ml-training) | DEMO | BETA | 1h | po-2023 | +| 38 | [2.9e-MIPS-Extraction-Programme.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9e-MIPS-Extraction-Programme.ipynb) | 2.9e — MIPS : du réseau au programme | Python 3 | READY | BETA | 45min | po-2023 | +| 39 | [3.0-Theorie-Information.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.0-Theorie-Information.ipynb) | 3.0 — Théorie de l'information : entropie, KL,… | Python 3 | READY | BETA | 30min | po-2023 | +| 40 | [3.1-Retropropagation.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.1-Retropropagation.ipynb) | 3.1 — La rétropropagation : la chaîne des… | Python 3 | READY | BETA | 30min | po-2023 | +| 41 | [3.10-Modeles-Generatifs-Diffusion-SOTA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.10-Modeles-Generatifs-Diffusion-SOTA.ipynb) | 3.10 — Le pendant SOTA : la bibliothèque diffusers… | Python 3 | READY | BETA | 45min | po-2023 | +| 42 | [3.11-Budget-Memoire-Entrainement.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.11-Budget-Memoire-Entrainement.ipynb) | 3.11 — Le budget mémoire d'un entraînement :… | Python 3 | DEMO | BETA | 1h | po-2023 | +| 43 | [3.12-Les-Collectives.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.12-Les-Collectives.ipynb) | 3.12 — Les collectives : l'anneau à la main contre… | Python 3 (coursia-ml-training) | READY | BETA | 45min | po-2023 | +| 44 | [3.13-Decouper-le-Modele-DDP-ZeRO-FSDP.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.13-Decouper-le-Modele-DDP-ZeRO-FSDP.ipynb) | 3.13 — Découper le modèle : DDP, ZeRO, FSDP — et… | Python 3 (coursia-ml-training) | DEMO | DRAFT | 45min | po-2023 | +| 45 | [3.2-Optimisateurs.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.2-Optimisateurs.ipynb) | 3.2 — Les optimisateurs : de SGD à Adam, ce qui… | Python 3 | READY | BETA | 30min | po-2023 | +| 46 | [3.3-Regularisation.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.3-Regularisation.ipynb) | 3.3 — Régularisation : dropout, weight decay,… | Python 3 | READY | BETA | 30min | po-2023 | +| 47 | [3.4-Attention-Transformer-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4-Attention-Transformer-From-Scratch.ipynb) | 3.4 — Attention et Transformer from scratch :… | Python 3 (coursia2) | READY | BETA | 45min | po-2023 | +| 48 | [3.4c-MoE-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4c-MoE-from-scratch.ipynb) | 3.4c — Mixture of Experts : router les jetons,… | Python 3 (coursia-ml-training) | READY | BETA | 45min | po-2023 | +| 49 | [3.5-Phenomenes-de-Generalisation.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.5-Phenomenes-de-Generalisation.ipynb) | 3.5 — Grokking et double descente : quand la… | Python 3 | READY | BETA | 30min | po-2023 | +| 50 | [3.6-Modeles-Generatifs.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6-Modeles-Generatifs.ipynb) | 3.6 — Modèles génératifs : trois objectifs, trois… | Python 3 | READY | BETA | 30min | po-2023 | +| 51 | [3.6b-Modeles-Generatifs-PyTorch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6b-Modeles-Generatifs-PyTorch.ipynb) | 3.6b — Modèles génératifs en PyTorch : VAE, GAN et… | Python 3 | READY | BETA | 45min | po-2023 | +| 52 | [3.6c-Modeles-Generatifs-Diffusion-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6c-Modeles-Generatifs-Diffusion-from-scratch.ipynb) | 3.6c — Modèles génératifs par diffusion : DDPM… | Python 3 (ipykernel) | DEMO | DRAFT | 1h | po-2023 | +| 53 | [3.6d-Modeles-Generatifs-Score-SDE-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6d-Modeles-Generatifs-Score-SDE-from-scratch.ipynb) | 3.6d — Modèles génératifs : Score-SDE *from… | Python 3 | DEMO | BETA | 1h | po-2023 | +| 54 | [3.6e-Modeles-Generatifs-Conditionnels-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6e-Modeles-Generatifs-Conditionnels-from-scratch.ipynb) | 3.6e — Génération conditionnelle et… | Python 3 | DEMO | BETA | 45min | po-2023 | +| 55 | [3.7-Distillation-Maitre-Eleve.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.7-Distillation-Maitre-Eleve.ipynb) | 3.7 — Distillation maître-élève : quand le savoir… | coursia-ml-training | READY | BETA | 30min | po-2023 | +| 56 | [3.8-Representations-Contrastives.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.8-Representations-Contrastives.ipynb) | Représentations contrastives modernes — du… | Python 3 | READY | BETA | 30min | po-2023 | +| 57 | [3.9-Compression-Quantization-FP.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9-Compression-Quantization-FP.ipynb) | 3.9 — Quantization FP : FP32 vers FP16 et BF16… | coursia-ml-training | READY | BETA | 45min | po-2023 | +| 58 | [3.9a-Compression-Quantization-INT8.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9a-Compression-Quantization-INT8.ipynb) | 3.9a — Compression par quantification INT8 : le… | Python 3 | READY | BETA | 45min | po-2023 | +| 59 | [3.9b-Compression-Pruning-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9b-Compression-Pruning-from-scratch.ipynb) | 3.9b — Compression par élagage : le réseau amputé… | Python 3 | DEMO | BETA | 1h | po-2023 | +| 60 | [3.9c-Pruning-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9c-Pruning-From-Scratch.ipynb) | 3.9c — Pruning from scratch : magnitude,… | Python 3 | DEMO | DRAFT | 45min | po-2023 | +| 61 | [3.9d-Compression-Distillation-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9d-Compression-Distillation-from-scratch.ipynb) | 3.9d — Compression par distillation : transférer… | Python 3 (coursia-ml-training) | DEMO | BETA | 45min | po-2023 | +| 62 | [3.9e-Compression-Quantization-SOTA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9e-Compression-Quantization-SOTA.ipynb) | 3.9e — Quantification SOTA : la même INT8, par… | Python 3 | READY | BETA | 45min | po-2023 | +| 63 | [3.9f-Compression-Pruning-SOTA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9f-Compression-Pruning-SOTA.ipynb) | 3.9f — Élagage SOTA : les mêmes masques, par… | Python 3 | READY | BETA | 45min | po-2023 | +| 64 | [3.9g-Compression-Comparatif-A-vs-B.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9g-Compression-Comparatif-A-vs-B.ipynb) | 3.9g — Comparatif compression : from scratch (Bloc… | Python 3 | READY | BETA | 45min | po-2023 | +| 65 | [4.1-Conv-NumPy-Torch-Allclose.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.1-Conv-NumPy-Torch-Allclose.ipynb) | 4.1 — Le neurone convolutif from scratch : kernel… | Python 3 | READY | BETA | 30min | po-2023 | +| 66 | [4.2-ConvNet-Profonde-Residuelles.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2-ConvNet-Profonde-Residuelles.ipynb) | 4.2 — ConvNet profonde : pourquoi les résiduelles | Python 3 | READY | BETA | 45min | po-2023 | +| 67 | [4.2b-Lean-GradientFlow-Vanishing.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2b-Lean-GradientFlow-Vanishing.ipynb) | Le gradient qui s'évanouit, le gradient qui survit… | Lean 4 (WSL) | READY | BETA | 30min | po-2023 | +| 68 | [4.2c-Detection-Anchor-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2c-Detection-Anchor-From-Scratch.ipynb) | 4.2c — Détection d'objets from scratch : la grille… | Python 3 | DEMO | BETA | 45min | po-2023 | +| 69 | [4.2d-Detection-AnchorFree-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2d-Detection-AnchorFree-From-Scratch.ipynb) | 4.2d — Détection d'objets anchor-free : le… | coursia-ml-training | READY | BETA | 45min | po-2023 | +| 70 | [4.2e-Detection-FocalLoss-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2e-Detection-FocalLoss-From-Scratch.ipynb) | 4.2e — Détection d'objets from scratch : la Focal… | Python 3 | READY | BETA | 30min | po-2023 | +| 71 | [4.2f-Detection-SOTA-Torchvision.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2f-Detection-SOTA-Torchvision.ipynb) | 4.2f — Détection SOTA : fine-tuner torchvision… | Python 3 | DEMO | BETA | 45min | po-2023 | +| 72 | [4.2g-Detection-SOTA-Ultralytics.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2g-Detection-SOTA-Ultralytics.ipynb) | 4.2g — Détection SOTA : YOLO sous ultralytics, la… | Python 3 | DEMO | BETA | 45min | po-2023 | +| 73 | [4.2h-YOLOv5-Bench-Ultralytics.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2h-YOLOv5-Bench-Ultralytics.ipynb) | 4.2h — Bench yolov5nu sur le terrain du 4.2c… | Python (coursia-ml-training) | READY | BETA | 30min | po-2023 | +| 74 | [4.2i-Detection-Ultralytics-Difficult-Scenes.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2i-Detection-Ultralytics-Difficult-Scenes.ipynb) | 4.2h — Détection SOTA : YOLO sous ultralytics,… | Python 3 (ipykernel) | DEMO | BETA | 45min | po-2023 | +| 75 | [4.2j-Detection-SOTA-LibreYOLO.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2j-Detection-SOTA-LibreYOLO.ipynb) | 4.2j — Détection SOTA : un second wrapper,… | Python 3 | READY | BETA | 45min | po-2023 | +| 76 | [4.3-TransferLearning-ResNet.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.3-TransferLearning-ResNet.ipynb) | 4.3 — Transfer learning : réutiliser un ResNet18… | Python 3 | READY | BETA | 45min | po-2023 | +| 77 | [WS-00a-Ondelettes-1D-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00a-Ondelettes-1D-from-scratch.ipynb) | WS-00a — Ondelettes 1D *from scratch* : analyse… | Python 3 | READY | BETA | 30min | po-2023 | +| 78 | [WS-00b-Ondelettes-2D-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00b-Ondelettes-2D-from-scratch.ipynb) | WS-00b — Ondelettes 2D *from scratch* : bandes… | Python 3 | READY | BETA | 30min | po-2023 | +| 79 | [WS-00c-Scattering-from-scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00c-Scattering-from-scratch.ipynb) | WS-00c — Scattering 2D *from scratch* : le module… | Python 3 | READY | BETA | 30min | po-2023 | +| 80 | [WS-01-Denoising-SOTA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-01-Denoising-SOTA.ipynb) | WS-01 — Débruitage d'images : du seuillage *from… | Python 3 | READY | BETA | 30min | po-2023 | +| 81 | [WS-02-Scattering-SOTA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-02-Scattering-SOTA.ipynb) | WS-02 — Scattering SOTA : kymatio contre le moteur… | Python 3 | READY | BETA | 45min | po-2023 | +| 82 | [WS-03-Synthese-Scattering-vs-ResNet.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-03-Synthese-Scattering-vs-ResNet.ipynb) | WS-03 — Synthèse : représentation construite vs… | Python 3 | READY | BETA | 30min | po-2023 | +| 83 | [Lab1-PythonForDataScience.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day1-Foundations/Labs/Lab1-PythonForDataScience.ipynb) | Lab 1 - Les Bases de la Data Science en Python | Python 3 | READY | BETA | 30min | po-2023 | +| 84 | [Lab2-RFP-Analysis.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day2-Document-Agents/Labs/Lab2-RFP-Analysis/Lab2-RFP-Analysis.ipynb) | Lab 2 - Analyser un Appel d'Offre avec l'IA | Python 3 | DEMO | BETA | 30min | po-2023 | +| 85 | [Lab3-CV-Screening.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day2-Document-Agents/Labs/Lab3-CV-Screening/Lab3-CV-Screening.ipynb) | Lab 3 - Pré-qualifier des Candidats avec l'IA | Python 3 | DEMO | BETA | 15min | po-2023 | +| 86 | [Lab4-DataWrangling.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab4-DataWrangling/Lab4-DataWrangling.ipynb) | Lab 4 - Le Nettoyage de Données avec Pandas | Python 3 | READY | BETA | 30min | po-2023 | +| 87 | [Lab5-Viz-ML.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab5-Viz-ML/Lab5-Viz-ML.ipynb) | Lab 5 - De la Visualisation au Machine Learning | Python 3 | READY | BETA | 30min | po-2023 | +| 88 | [Lab6-First-Agent.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab6-First-Agent/Lab6-First-Agent.ipynb) | Lab 6 - Anatomie de votre premier Agent d'IA | Python 3 | DEMO | BETA | 30min | po-2023 | +| 89 | [Lab7-Data-Analysis-Agent.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab7-Data-Analysis-Agent/Lab7-Data-Analysis-Agent.ipynb) | Lab 7 - Votre premier Agent Analyste de Données | Python 3 | READY | BETA | 30min | po-2023 | +| 90 | [Lab8-ADK-Introduction.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day4-Foundations/Lab8-ADK-Introduction.ipynb) | Lab 8: Introduction au Framework ADK et… | Python 3 | DEMO | BETA | 30min | po-2023 | +| 91 | [Lab9-First-ADK-Agent.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day4-Foundations/Lab9-First-ADK-Agent.ipynb) | Lab 9: Premier Agent ADK pour Data Science | Python 3 | READY | BETA | 30min | po-2023 | +| 92 | [Lab10-File-Analyzer.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab10-File-Analyzer.ipynb) | Lab 10: Data File Analyzer (DS-STAR Component) | Python 3 | READY | BETA | 30min | po-2023 | +| 93 | [Lab11-Planner-Coder-Loop.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab11-Planner-Coder-Loop.ipynb) | Lab 11: Planner-Coder-Verifier Loop (DS-STAR Core) | Python 3 | READY | ALPHA | 45min | po-2023 | +| 94 | [Lab12-DS-Star-Workshop.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12-DS-Star-Workshop.ipynb) | Lab 12: DS-STAR Workshop - Analyse Multi-Fichiers | Python 3 | READY | BETA | 45min | po-2023 | +| 95 | [Lab12b-Sequential-Orchestration.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12b-Sequential-Orchestration.ipynb) | Lab 12b : Désignation séquentielle — le contrat… | Python 3 | READY | BETA | 30min | po-2023 | +| 96 | [Lab12c-Agent-Handoff.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12c-Agent-Handoff.ipynb) | Lab 12c : Handoff entre agents — le contrat C5, le… | Python 3 | READY | BETA | 30min | po-2023 | +| 97 | [Lab12d-Token-Usage.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12d-Token-Usage.ipynb) | Lab 12d : Tracabilite de la consommation — le… | Python 3 | READY | BETA | 30min | po-2023 | +| 98 | [Lab12e-Session-Persistence.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12e-Session-Persistence.ipynb) | Lab 12e: Persistance d'etat de session - une… | Python 3 (ipykernel) | DEMO | BETA | 30min | po-2023 | +| 99 | [Lab13-Web-Search-SOTA.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab13-Web-Search-SOTA.ipynb) | Lab 13: Web Search pour Modèles SOTA (MLE-STAR… | Python 3 | READY | BETA | 30min | po-2023 | +| 100 | [Lab14-Ablation-Refinement.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab14-Ablation-Refinement.ipynb) | Lab 14: Ablation et Raffinement Ciblé (MLE-STAR… | Python 3 | READY | ALPHA | 30min | po-2023 | +| 101 | [Lab15-Kaggle-Challenge.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab15-Kaggle-Challenge.ipynb) | Lab 15: Kaggle Challenge avec MLE-STAR | Python 3 | READY | BETA | 30min | po-2023 | +| 102 | [Lab16-Data-Science-Agent.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day7-Production/Lab16-Data-Science-Agent.ipynb) | Lab 16: Data Science Agent avec GCP BigQuery | Python 3 | READY | ALPHA | 30min | po-2023 | +| 103 | [Lab17-Final-Project.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day7-Production/Lab17-Final-Project.ipynb) | Lab 17: Projet Final - Pipeline DS-STAR Complet | Python 3 | READY | ALPHA | 45min | po-2023 | #### ML.Net (23) @@ -714,7 +737,7 @@ Total notebooks: 1312 | 22 | [ML-9-Anomaly-Detection.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-9-Anomaly-Detection.ipynb) | ML-9 : Detection d'anomalies avec Randomized PCA | .NET (C#) | READY | BETA | 45min | po-2023 | | 23 | [TP-prevision-ventes.ipynb](MyIA.AI.Notebooks/ML/ML.Net/TP-prevision-ventes.ipynb) | TP : Prevision des ventes d'assurance | .NET (C#) | READY | BETA | 30min | po-2023 | -### SymbolicAI (307 notebooks) — DEMO:7, READY:300 | ALPHA:7, BETA:296, DRAFT:4 +### SymbolicAI (312 notebooks) — DEMO:5, READY:307 | ALPHA:9, BETA:299, DRAFT:4 #### Racine (1) @@ -722,131 +745,129 @@ Total notebooks: 1312 |---|----------|-------|--------|--------|----------|----------|-------| | 1 | [OR-tools-Stiegler.ipynb](MyIA.AI.Notebooks/SymbolicAI/OR-tools-Stiegler.ipynb) | Configuration de l'environnement C# | .NET (C#) | READY | BETA | 45min | po-2024 | -#### Argument_Analysis (36) +#### Argument_Analysis (32) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| -| 1 | [Argument_Analysis_Agentic-0-init_agent.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Agentic-0-init_agent.ipynb) | Analyse rhétorique collaborative par agents IA… | Python 3 | DEMO | BETA | 30min | po-2024 | -| 2 | [Argument_Analysis_Agentic-1-informal_agent.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Agentic-1-informal_agent.ipynb) | Agent InformalAnalysisAgent (définitions) | Python 3 | READY | BETA | 15min | po-2024 | -| 3 | [Argument_Analysis_Agentic-2-pl_agent.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Agentic-2-pl_agent.ipynb) | Agent PropositionalLogicAgent (définitions) | Python 3 | READY | BETA | 15min | po-2024 | -| 4 | [Argument_Analysis_Agentic-3-orchestration_agent.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Agentic-3-orchestration_agent.ipynb) | Orchestration de la conversation multi-agents | Python 3 | DEMO | BETA | 15min | po-2024 | -| 5 | [Argument_Analysis_Dated_Graphs.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Dated_Graphs.ipynb) | Graphes d'argumentation datés — l'instrument… | Python 3 | READY | BETA | 45min | po-2024 | -| 6 | [Argument_Analysis_Fallacy_Rules_Symboliques.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Fallacy_Rules_Symboliques.ipynb) | Détection symbolique de sophismes — l'étage… | Python 3 | READY | BETA | 30min | po-2024 | -| 7 | [Argument_Analysis_Gouvernance_Multi_Agents.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Gouvernance_Multi_Agents.ipynb) | Gouvernance multi-agents : scrutins, protocoles,… | Python 3 | READY | BETA | 30min | po-2024 | -| 8 | [Argument_Analysis_Observatoire-1-Initiation.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Observatoire-1-Initiation.ipynb) | Observatoire des formes relationnelles — Cas 1 | Python 3 | READY | BETA | 30min | po-2024 | -| 9 | [Argument_Analysis_Ontology_AIF.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Ontology_AIF.ipynb) | Ontologie AIF.owl — l'architecture Argumentum des… | Python 3 | READY | ALPHA | 45min | po-2024 | -| 10 | [Argument_Analysis_Ontology_CrossLinks.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Ontology_CrossLinks.ipynb) | Liens croisés crossLink et attaques AIF du CSV… | Python 3 | READY | BETA | 30min | po-2024 | -| 11 | [Argument_Analysis_Ontology_Virtues.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Ontology_Virtues.ipynb) | Ontologie des vertus argumentatives — le pôle… | Python 3 | READY | BETA | 30min | po-2024 | -| 12 | [Argument_Analysis_Recollement_Lectures.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Recollement_Lectures.ipynb) | Strate 6 : le banc de recollement | Python 3 | READY | BETA | 30min | po-2024 | -| 13 | [Argument_Analysis_Recollement_Strate6.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Recollement_Strate6.ipynb) | Strate 6 : le recollement sur lectures réellement… | Python 3 | READY | BETA | 45min | po-2024 | -| 14 | [Argumentation-00-Setup-Tweety-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-00-Setup-Tweety-Python.ipynb) | Configuration de l'environnement (JVM Tweety… | Python 3 | READY | BETA | 15min | po-2024 | -| 15 | [Argumentation-01-Toulmin-Model-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-01-Toulmin-Model-Python.ipynb) | Le modèle de Toulmin (1958) | Python 3 | READY | BETA | 15min | po-2024 | -| 16 | [Argumentation-01b-Schemes-Walton-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-01b-Schemes-Walton-Python.ipynb) | Reconnaître un schéma d'argumentation — la table… | Python 3 | READY | BETA | 30min | po-2024 | -| 17 | [Argumentation-02-Fallacies-Detection-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-02-Fallacies-Detection-Python.ipynb) | Détection de sophismes par taxonomie | Python 3 | READY | BETA | 30min | po-2024 | -| 18 | [Argumentation-02b-Argumentum-Cards-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-02b-Argumentum-Cards-Python.ipynb) | Argumentum : la carte de sophisme, du nœud de… | Python 3 | READY | BETA | 30min | po-2024 | -| 19 | [Argumentation-03-Dung-AF-Semantics-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-03-Dung-AF-Semantics-Python.ipynb) | Argumentation abstraite de Dung — sémantiques… | Python 3 | READY | BETA | 45min | po-2024 | -| 20 | [Argumentation-03b-Value-Based-AF-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-03b-Value-Based-AF-Python.ipynb) | Argumentation basée sur les valeurs (VAF,… | Python 3 | READY | BETA | 15min | po-2024 | -| 21 | [Argumentation-03c-Ranking-Semantics-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-03c-Ranking-Semantics-Python.ipynb) | Argumentation graduée — sémantiques de classement… | Python 3 | READY | BETA | 30min | po-2024 | -| 22 | [Argumentation-04-Dialogues-Protocolises-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-04-Dialogues-Protocolises-Python.ipynb) | Dialogues protocolisés : inquiry et persuasion… | Python 3 (ipykernel) | READY | BETA | 45min | po-2024 | -| 23 | [Argumentation-04b-Knowledge-Base-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-04b-Knowledge-Base-Python.ipynb) | La base de connaissances d'un débat —… | Python 3 | READY | BETA | 30min | po-2024 | -| 24 | [Argumentation-05-Formal-Verification-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-05-Formal-Verification-Python.ipynb) | Vérification logique formelle avec Tweety | Python 3 | READY | BETA | 30min | po-2024 | -| 25 | [Argumentation-05b-Multi-Backend-Routing-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-05b-Multi-Backend-Routing-Python.ipynb) | Routage multi-backend : décider ou échouer… | Python 3 | READY | BETA | 30min | po-2024 | -| 26 | [Argumentation-05c-Formal-Richness-Matrix-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-05c-Formal-Richness-Matrix-Python.ipynb) | Matrice de richesse formelle — évaluer honnêtement… | Python 3 | READY | DRAFT | 30min | po-2024 | -| 27 | [Argumentation-06-JTMS-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-06-JTMS-Python.ipynb) | Truth Maintenance System (JTMS) déterministe | Python 3 | READY | BETA | 30min | po-2024 | -| 28 | [Argumentation-07-Orchestration-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-07-Orchestration-Python.ipynb) | Deux paradigmes d'orchestration | Python 3 | READY | BETA | 30min | po-2024 | -| 29 | [Argumentation-07b-Communication-Channels-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-07b-Communication-Channels-Python.ipynb) | Le bus de communication multi-agents — le contrat,… | Python 3 | READY | BETA | 30min | po-2024 | -| 30 | [Argumentation-07c-Orchestration-Modes-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-07c-Orchestration-Modes-Python.ipynb) | Orchestration d'un debat : arbitrer entre sept… | Python 3 | READY | BETA | 30min | po-2024 | -| 31 | [Argumentation-08-Capstone-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08-Capstone-Python.ipynb) | Capstone d'intégration (baseline 0-shot vs… | Python 3 | READY | BETA | 30min | po-2024 | -| 32 | [Argumentation-08b-Executor-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08b-Executor-Python.ipynb) | Analyse rhétorique collaborative par agents IA —… | Python 3 | READY | BETA | 30min | po-2024 | -| 33 | [Argumentation-08c-UI-Configuration-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08c-UI-Configuration-Python.ipynb) | Interface de configuration et préparation du texte | Python 3 | READY | BETA | 30min | po-2024 | -| 34 | [Argumentation-08d-Restitution-3-Actes-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08d-Restitution-3-Actes-Python.ipynb) | Restitution en 3 actes — scaffold déterministe,… | Python 3 (ipykernel) | DEMO | BETA | 45min | po-2024 | -| 35 | [Argumentation-08e-Argument-Profile-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08e-Argument-Profile-Python.ipynb) | ArgumentProfile : la fiche d'identité… | Python 3 | READY | BETA | 30min | po-2024 | -| 36 | [I2_Contre_arguments_ASPIC.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/groupe-I2-contre-arguments-aspic/I2_Contre_arguments_ASPIC.ipynb) | I2 — Génération de contre-arguments par… | Python 3 | READY | BETA | 45min | po-2024 | - -#### Geometry (4) +| 1 | [Argument_Analysis_Fallacy_Rules_Symboliques.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Fallacy_Rules_Symboliques.ipynb) | Détection symbolique de sophismes — l'étage… | Python 3 | READY | BETA | 30min | po-2024 | +| 2 | [Argument_Analysis_Gouvernance_Multi_Agents.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Gouvernance_Multi_Agents.ipynb) | Gouvernance multi-agents : scrutins, protocoles,… | Python 3 | READY | BETA | 30min | po-2024 | +| 3 | [Argumentation-00-Setup-Tweety-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-00-Setup-Tweety-Python.ipynb) | Configuration de l'environnement (JVM Tweety… | Python 3 | READY | BETA | 15min | po-2024 | +| 4 | [Argumentation-01-Toulmin-Model-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-01-Toulmin-Model-Python.ipynb) | Le modèle de Toulmin (1958) | Python 3 | READY | BETA | 15min | po-2024 | +| 5 | [Argumentation-01b-Schemes-Walton-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-01b-Schemes-Walton-Python.ipynb) | Reconnaître un schéma d'argumentation — la table… | Python 3 | READY | BETA | 30min | po-2024 | +| 6 | [Argumentation-02-Fallacies-Detection-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-02-Fallacies-Detection-Python.ipynb) | Détection de sophismes par taxonomie | Python 3 | READY | BETA | 30min | po-2024 | +| 7 | [Argumentation-02b-Argumentum-Cards-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-02b-Argumentum-Cards-Python.ipynb) | Argumentum : la carte de sophisme, du nœud de… | Python 3 | READY | BETA | 30min | po-2024 | +| 8 | [Argumentation-03-Dung-AF-Semantics-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-03-Dung-AF-Semantics-Python.ipynb) | Argumentation abstraite de Dung — sémantiques… | Python 3 | READY | BETA | 45min | po-2024 | +| 9 | [Argumentation-03b-Value-Based-AF-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-03b-Value-Based-AF-Python.ipynb) | Argumentation basée sur les valeurs (VAF,… | Python 3 | READY | BETA | 15min | po-2024 | +| 10 | [Argumentation-03c-Ranking-Semantics-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-03c-Ranking-Semantics-Python.ipynb) | Argumentation graduée — sémantiques de classement… | Python 3 | READY | BETA | 30min | po-2024 | +| 11 | [Argumentation-04-Dialogues-Protocolises-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-04-Dialogues-Protocolises-Python.ipynb) | Dialogues protocolisés : inquiry et persuasion… | Python 3 (ipykernel) | READY | BETA | 45min | po-2024 | +| 12 | [Argumentation-04b-Knowledge-Base-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-04b-Knowledge-Base-Python.ipynb) | La base de connaissances d'un débat —… | Python 3 | READY | BETA | 30min | po-2024 | +| 13 | [Argumentation-05-Formal-Verification-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-05-Formal-Verification-Python.ipynb) | Vérification logique formelle avec Tweety | Python 3 | READY | BETA | 30min | po-2024 | +| 14 | [Argumentation-05b-Multi-Backend-Routing-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-05b-Multi-Backend-Routing-Python.ipynb) | Routage multi-backend : décider ou échouer… | Python 3 | READY | BETA | 30min | po-2024 | +| 15 | [Argumentation-05c-Formal-Richness-Matrix-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-05c-Formal-Richness-Matrix-Python.ipynb) | Matrice de richesse formelle — évaluer honnêtement… | Python 3 | READY | DRAFT | 30min | po-2024 | +| 16 | [Argumentation-06-JTMS-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-06-JTMS-Python.ipynb) | Truth Maintenance System (JTMS) déterministe | Python 3 | READY | BETA | 30min | po-2024 | +| 17 | [Argumentation-07-Orchestration-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-07-Orchestration-Python.ipynb) | Deux paradigmes d'orchestration | Python 3 | READY | BETA | 30min | po-2024 | +| 18 | [Argumentation-07b-Communication-Channels-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-07b-Communication-Channels-Python.ipynb) | Le bus de communication multi-agents — le contrat,… | Python 3 | READY | BETA | 30min | po-2024 | +| 19 | [Argumentation-07c-Orchestration-Modes-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-07c-Orchestration-Modes-Python.ipynb) | Orchestration d'un debat : arbitrer entre sept… | Python 3 | READY | BETA | 30min | po-2024 | +| 20 | [Argumentation-08-Capstone-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08-Capstone-Python.ipynb) | Capstone d'intégration (baseline 0-shot vs… | Python 3 | READY | BETA | 45min | po-2024 | +| 21 | [Argumentation-08b-Executor-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08b-Executor-Python.ipynb) | Analyse rhétorique collaborative par agents IA —… | Python 3 | READY | BETA | 30min | po-2024 | +| 22 | [Argumentation-08c-UI-Configuration-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08c-UI-Configuration-Python.ipynb) | Interface de configuration et préparation du texte | Python 3 | READY | BETA | 30min | po-2024 | +| 23 | [Argumentation-08d-Restitution-3-Actes-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08d-Restitution-3-Actes-Python.ipynb) | Restitution en 3 actes — scaffold déterministe,… | Python 3 (ipykernel) | DEMO | BETA | 45min | po-2024 | +| 24 | [Argumentation-08e-Argument-Profile-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08e-Argument-Profile-Python.ipynb) | ArgumentProfile : la fiche d'identité… | Python 3 | READY | BETA | 30min | po-2024 | +| 25 | [Argumentation-Obs-01-Graphes-Dates-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Obs-01-Graphes-Dates-Python.ipynb) | Graphes d'argumentation datés — l'instrument… | Python 3 | READY | BETA | 45min | po-2024 | +| 26 | [Argumentation-Obs-02-Initiation-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Obs-02-Initiation-Python.ipynb) | Observatoire des formes relationnelles — Cas 1 | Python 3 | READY | BETA | 30min | po-2024 | +| 27 | [Argumentation-Obs-03-Recollement-Lectures-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Obs-03-Recollement-Lectures-Python.ipynb) | Strate 6 : le banc de recollement | Python 3 | READY | BETA | 30min | po-2024 | +| 28 | [Argumentation-Obs-04-Recollement-Strate6-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Obs-04-Recollement-Strate6-Python.ipynb) | Strate 6 : le recollement sur lectures réellement… | Python 3 | READY | BETA | 45min | po-2024 | +| 29 | [Argumentation-Onto-01-AIF-OWL2-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Onto-01-AIF-OWL2-Python.ipynb) | Ontologie AIF.owl — l'architecture Argumentum des… | Python 3 | READY | ALPHA | 45min | po-2024 | +| 30 | [Argumentation-Onto-02-CrossLinks-CSV-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Onto-02-CrossLinks-CSV-Python.ipynb) | Liens croisés crossLink et attaques AIF du CSV… | Python 3 | READY | BETA | 30min | po-2024 | +| 31 | [Argumentation-Onto-03-Vertus-SKOS-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Onto-03-Vertus-SKOS-Python.ipynb) | Ontologie des vertus argumentatives — le pôle… | Python 3 | READY | BETA | 30min | po-2024 | +| 32 | [I2_Contre_arguments_ASPIC.ipynb](MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/groupe-I2-contre-arguments-aspic/I2_Contre_arguments_ASPIC.ipynb) | I2 — Génération de contre-arguments par… | Python 3 | READY | BETA | 45min | po-2024 | + +#### Lean (82) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| -| 1 | [Geometry-01-From-Figure-To-Equation.ipynb](MyIA.AI.Notebooks/SymbolicAI/Geometry/Geometry-01-From-Figure-To-Equation.ipynb) | Geometry 01 — De la figure à l'équation | Python 3 | READY | BETA | 30min | po-2024 | -| 2 | [Geometry-02-From-Equation-To-Proof.ipynb](MyIA.AI.Notebooks/SymbolicAI/Geometry/Geometry-02-From-Equation-To-Proof.ipynb) | Geometry 02 — Prouver par l'algèbre | Python 3 | READY | BETA | 45min | po-2024 | -| 3 | [Geometry-03-Wu-Method-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Geometry/Geometry-03-Wu-Method-Python.ipynb) | Geometry 03 — La méthode de Wu | Python 3 | READY | BETA | 45min | po-2024 | -| 4 | [Geometry-03b-Ritt-Decomposition-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Geometry/Geometry-03b-Ritt-Decomposition-Python.ipynb) | Geometry 03b — Décomposition de Ritt et… | Python 3 (ipykernel) | READY | BETA | 45min | po-2024 | - -#### Lean (71) - -| # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | -|---|----------|-------|--------|--------|----------|----------|-------| -| 1 | [01-formes-modulaires-sl2z-hecke.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Langlands/01-formes-modulaires-sl2z-hecke.ipynb) | Langlands 01 : formes modulaires — de SL₂(ℤ) aux… | Python 3 | READY | BETA | 30min | po-2024 | -| 2 | [Lean-1-Setup.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-1-Setup.ipynb) | Lean 4 - Installation et Configuration | Python 3 (WSL) | READY | BETA | 30min | po-2024 | -| 3 | [Lean-10-LeanDojo.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-10-LeanDojo.ipynb) | Lean 10 : LeanDojo - ML/LLM Theorem Proving | Python 3 (WSL) | READY | BETA | 45min | po-2024 | -| 4 | [Lean-11-TorchLean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-11-TorchLean.ipynb) | Lean 11 - TorchLean : Réseaux de Neurones… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 5 | [Lean-11b-TorchLean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-11b-TorchLean-Python.ipynb) | Lean 11b - TorchLean : Implémentation Python des… | Python 3 | READY | BETA | 45min | po-2024 | -| 6 | [Lean-12-Sensitivity-Theorem.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12-Sensitivity-Theorem.ipynb) | Lean-12 : Le Théorème de Sensibilité (Huang 2019) | Python 3 | READY | BETA | 30min | po-2024 | -| 7 | [Lean-12b-Lean-Sensitivity-Theorem.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12b-Lean-Sensitivity-Theorem.ipynb) | Lean-12b — Théorème de Sensibilité de Huang… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 8 | [Lean-13-Kochen-Specker.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13-Kochen-Specker.ipynb) | Lean-13 : Le Théorème de Kochen-Specker (Cabello… | Python 3 | READY | BETA | 30min | po-2024 | -| 9 | [Lean-13b-CHSH-Tsirelson-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13b-CHSH-Tsirelson-Native.ipynb) | Lean-13b : la borne de Tsirelson — digestion… | Lean 4 (WSL, conway-build) | READY | BETA | 30min | po-2024 | -| 10 | [Lean-13c-CHSH-Landau-Saturation.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13c-CHSH-Landau-Saturation.ipynb) | Lean-13c : la saturation de Tsirelson — le témoin… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 11 | [Lean-14-Finiteness-Derivatives.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-14-Finiteness-Derivatives.ipynb) | Lean-14 — Dérivées symboliques de Brzozowski : la… | Python 3 | READY | DRAFT | 15min | po-2024 | -| 12 | [Lean-14b-Finiteness-Lean-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-14b-Finiteness-Lean-Companion.ipynb) | Lean-14b - Finiteness des dérivées de Brzozowski —… | Lean 4 (WSL) | READY | DRAFT | 30min | po-2024 | -| 13 | [Lean-15-Grothendieck-Tribute.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15-Grothendieck-Tribute.ipynb) | Lean-15 : Hommage a Alexandre Grothendieck -- Le… | Python 3 | READY | BETA | 30min | po-2024 | -| 14 | [Lean-15b-Lean-Grothendieck.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15b-Lean-Grothendieck.ipynb) | Lean-15b : Grothendieck en Lean -- Atelier… | Python 3 | READY | BETA | 45min | po-2024 | -| 15 | [Lean-15c-Lean-Grothendieck-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15c-Lean-Grothendieck-Companion.ipynb) | Lean-15c : le lake Grothendieck par ses énoncés… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | -| 16 | [Lean-16a-Conway-Man-and-Work.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16a-Conway-Man-and-Work.ipynb) | Lean-16a - Conway, l'homme et l'oeuvre | Python 3 (ipykernel) | READY | BETA | 45min | po-2024 | -| 17 | [Lean-16b-Conway-Game-of-Life-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16b-Conway-Game-of-Life-Lean.ipynb) | Lean-16b : Hommage a John Conway — Game of Life as… | Python 3 (ipykernel) | READY | BETA | 45min | po-2024 | -| 18 | [Lean-16c-Conway-Game-of-Life-Golly.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16c-Conway-Game-of-Life-Golly.ipynb) | Lean-16c - Conway Game of Life : les 3 piliers, en… | Python 3 | READY | BETA | 45min | po-2024 | -| 19 | [Lean-16d-Conway-Game-of-Life-Lean-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16d-Conway-Game-of-Life-Lean-Native.ipynb) | Lean-16d : Game of Life sur kernel Lean natif | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 20 | [Lean-16e-Conway-FRACTRAN-Lean-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16e-Conway-FRACTRAN-Lean-Native.ipynb) | Lean-16e : FRACTRAN, la machine universelle de… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 21 | [Lean-16f-Conway-Free-Will-Theorem.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16f-Conway-Free-Will-Theorem.ipynb) | Lean-16f : Le Théorème du Libre Arbitre… | Python 3 | READY | BETA | 45min | po-2024 | -| 22 | [Lean-16g-Conway-Canons.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16g-Conway-Canons.ipynb) | Lean 16g — Canons : le barreau 2 de l'échelle des… | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | -| 23 | [Lean-16h-Conway-PatternTour-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16h-Conway-PatternTour-Native.ipynb) | Lean-16h : la tournée des motifs du Jeu de la Vie… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 24 | [Lean-16i-Translateur-Life.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16i-Translateur-Life.ipynb) | Lean-16i — Synthèse d'un translateur minuscule :… | Python 3 | READY | BETA | 15min | po-2024 | -| 25 | [Lean-16j-Conway-Hashlife-Correctness-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16j-Conway-Hashlife-Correctness-Native.ipynb) | Lean-16j : la preuve de correction Hashlife —… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | -| 26 | [Lean-17a-Knots-Conway-Proofs.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17a-Knots-Conway-Proofs.ipynb) | Lean 17a — Conway, les Nœuds et la Preuve de… | Python 3 | READY | BETA | 30min | po-2024 | -| 27 | [Lean-17b-Knots-Invariants-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17b-Knots-Invariants-Companion.ipynb) | Lean 17b — Invariants de Nœuds : Calcul et… | Python 3 | READY | BETA | 45min | po-2024 | -| 28 | [Lean-17c-Knots-Companion-Formel.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17c-Knots-Companion-Formel.ipynb) | Lean 17c — Le lake knot_lean par ses déclarations… | Python 3 | READY | BETA | 30min | po-2024 | -| 29 | [Lean-18-Sendov-Complex-Analysis.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-18-Sendov-Complex-Analysis.ipynb) | Lean-18 : La Conjecture de Sendov (preuve L.… | Python 3 | READY | BETA | 30min | po-2024 | -| 30 | [Lean-19-Analysis-I-Tao-Workflow.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-19-Analysis-I-Tao-Workflow.ipynb) | Lean-19 : Le manuel *Analysis I* de T. Tao en Lean… | Python 3 | READY | BETA | 30min | po-2024 | -| 31 | [Lean-2-Dependent-Types.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-2-Dependent-Types.ipynb) | Lean 2 - Types Dependants et Calcul des… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | -| 32 | [Lean-20-PFR-Entropy-Method.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-20-PFR-Entropy-Method.ipynb) | Lean-20 : La conjecture de Freiman-Ruzsa… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 33 | [Lean-20b-PFR-Primitives-Transportables.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-20b-PFR-Primitives-Transportables.ipynb) | Lean-20b : Trois primitives de PFR, et l'endroit… | Python 3 | READY | BETA | 15min | po-2024 | -| 34 | [Lean-21-MIMO-Detection-Flips.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21-MIMO-Detection-Flips.ipynb) | Lean-21 : Detection MIMO par flips -- le seuil 2… | Python 3 | READY | BETA | 30min | po-2024 | -| 35 | [Lean-21b-MIMO-Converse-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21b-MIMO-Converse-Native.ipynb) | Lean-21b : le lake mimo_lean par ses énoncés —… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | -| 36 | [Lean-21c-Descente-Budget.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21c-Descente-Budget.ipynb) | Lean-21c : Le budget de descente - quand la… | Python 3 | READY | BETA | 30min | po-2024 | -| 37 | [Lean-22-Galois-Probleme-Inverse-M23.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-22-Galois-Probleme-Inverse-M23.ipynb) | Lean-22 : Le problème inverse de Galois — M₂₃… | Python 3 | READY | BETA | 45min | po-2024 | -| 38 | [Lean-23-ERC20-Invariant-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-23-ERC20-Invariant-Companion.ipynb) | Lean-23 : ERC-20 sous Lean 4 — l'invariant de… | Python3 | READY | BETA | 15min | po-2024 | -| 39 | [Lean-23b-Lean-ERC20-Native-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-23b-Lean-ERC20-Native-Companion.ipynb) | Lean-23b — ERC-20 natif : l'invariant de… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 40 | [Lean-24-Calibration-Native-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-24-Calibration-Native-Companion.ipynb) | Lean-24 : le lake calibration_lean par ses énoncés… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 41 | [Lean-24b-Confiance-Preuves-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-24b-Confiance-Preuves-Native.ipynb) | Lean-24b : Confiance et preuves — quand un… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 42 | [Lean-25-Coherence-et-Temoin.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-25-Coherence-et-Temoin.ipynb) | Lean-25 — Cohérence et témoin : de Finetti… | Python 3 | READY | BETA | 30min | po-2024 | -| 43 | [Lean-26-Munkres-Tribute.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-26-Munkres-Tribute.ipynb) | Lean-26 : Hommage à James R. Munkres — le cours… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 44 | [Lean-27-EdgeColoring-Tutte-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-27-EdgeColoring-Tutte-Companion.ipynb) | Lean-27 : coloration d'arêtes et conjecture de… | Lean 4 (WSL) | READY | BETA | 15min | po-2024 | -| 45 | [Lean-28-Complex-Structure-S6.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-28-Complex-Structure-S6.ipynb) | Lean-28 : Le problème de Hopf sur S⁶ — digestion… | Python 3 | READY | BETA | 30min | po-2024 | -| 46 | [Lean-29-Hecke-Operators-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-29-Hecke-Operators-Native.ipynb) | Lean-29 : les opérateurs de Hecke $T_p$ et $U_p$ —… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | -| 47 | [Lean-3-Propositions-Proofs.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-3-Propositions-Proofs.ipynb) | Lean 3 - Propositions et Preuves | Lean 4 | READY | BETA | 45min | po-2024 | -| 48 | [Lean-30-FormalGroups-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-30-FormalGroups-Native.ipynb) | Lean-30 : groupes formels multivariés — compagnon… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 49 | [Lean-31-Euler-Navier-Stokes.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-31-Euler-Navier-Stokes.ipynb) | Lean-31 : Euler et Navier–Stokes — reproduction… | Python 3 | READY | BETA | 45min | po-2024 | -| 50 | [Lean-33-Distribution-Spaces.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-33-Distribution-Spaces.ipynb) | Lean-33 : espaces de Schwartz — décroissance et… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 51 | [Lean-34-Calculabilite-et-Limites.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-34-Calculabilite-et-Limites.ipynb) | Lean-34 — Calculabilité et limites : de l'arrêt… | Python 3 | READY | BETA | 30min | po-2024 | -| 52 | [Lean-34b-FairBot-Loeb.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-34b-FairBot-Loeb.ipynb) | Lean-34b — FairBot par le théorème de Löb :… | Python 3 | READY | BETA | 30min | po-2024 | -| 53 | [Lean-36-Structures-Finies-MUH-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-36-Structures-Finies-MUH-Lean.ipynb) | Lean-36 : structures mathematiques finies —… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 54 | [Lean-37-Capstone-Serre100.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-37-Capstone-Serre100.ipynb) | Lean-37 : Capstone — la sous-série « Serre 100 » | Python 3 | READY | BETA | 15min | po-2024 | -| 55 | [Lean-3b-Formalized-Formal-Logic.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-3b-Formalized-Formal-Logic.ipynb) | Lean-3b — Formalized Formal Logic : le laboratoire… | Python 3 | READY | BETA | 30min | po-2024 | -| 56 | [Lean-4-Quantifiers.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-4-Quantifiers.ipynb) | Lean 4 - Quantificateurs et Logique du Premier… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | -| 57 | [Lean-5-Tactics.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-5-Tactics.ipynb) | Lean 5 - Mode Tactique | Lean 4 | READY | BETA | 1h | po-2024 | -| 58 | [Lean-6-Mathlib-Essentials.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-6-Mathlib-Essentials.ipynb) | Lean 6 - Mathlib4 : La Bibliotheque Mathematique | Lean 4 | READY | BETA | 45min | po-2024 | -| 59 | [Lean-7-LLM-Integration.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-7-LLM-Integration.ipynb) | Lean 7 - Integration des LLMs pour l'Assistance… | Python 3 (WSL) | READY | BETA | 45min | po-2024 | -| 60 | [Lean-7b-Examples.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-7b-Examples.ipynb) | Lean 7b - Exemples Progressifs et Benchmarks | Python 3 (WSL) | READY | BETA | 30min | po-2024 | -| 61 | [Lean-8-Agentic-Proving.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-8-Agentic-Proving.ipynb) | Lean-8 - Agents Autonomes pour Demonstration de… | Python 3 | READY | BETA | 30min | po-2024 | -| 62 | [Lean-8b-Erdos-Formal-Conjectures-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-8b-Erdos-Formal-Conjectures-Native.ipynb) | Lean 8b : le programme Erdős et le pattern… | Lean 4 (WSL,… | READY | BETA | 30min | po-2024 | -| 63 | [Lean-9-SK-Multi-Agents.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-9-SK-Multi-Agents.ipynb) | Lean 9 : Multi-Agents avec Semantic Kernel | Python 3 | READY | BETA | 45min | po-2024 | -| 64 | [01-corps-finis-borne-hasse.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/01-corps-finis-borne-hasse.ipynb) | Corps finis et la borne de Hasse — distiller un… | Python 3 | READY | BETA | 30min | po-2024 | -| 65 | [02-valeurs-zeta-multiples-finies.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/02-valeurs-zeta-multiples-finies.ipynb) | 2. Valeurs zêta multiples finies — l'anneau des… | Python 3 | READY | BETA | 30min | po-2024 | -| 66 | [03-cohomologie-cech-espaces-finis.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/03-cohomologie-cech-espaces-finis.ipynb) | Cohomologie de Čech calculée — espaces… | Python 3 | READY | BETA | 30min | po-2024 | -| 67 | [04-lemme-yoneda-categories-finies.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/04-lemme-yoneda-categories-finies.ipynb) | Lemme de Yoneda calculé — catégories finies | Python 3 | READY | BETA | 30min | po-2024 | -| 68 | [05-table-de-caracteres.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/05-table-de-caracteres.ipynb) | 5. Tables de caractères — le squelette… | Python 3 | READY | BETA | 45min | po-2024 | -| 69 | [06-bulles-minkowski.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/06-bulles-minkowski.ipynb) | Les bulles diaboliques de Minkowski — géométrie… | Python 3 | READY | BETA | 30min | po-2024 | -| 70 | [07-zeros-fonctions-l-gaps-gue.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/07-zeros-fonctions-l-gaps-gue.ipynb) | Zéros de fonctions L, gaps et statistique GUE | Python 3 | READY | BETA | 45min | po-2024 | -| 71 | [08-serre-dans-mathlib.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/08-serre-dans-mathlib.ipynb) | Serre dans Mathlib — tour guidé des cinq monuments | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 1 | [ANALYSE-01-Sendov-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-01-Sendov-Lean-Python.ipynb) | ANALYSE-01 : La Conjecture de Sendov (preuve L.… | Python 3 | READY | BETA | 30min | po-2024 | +| 2 | [ANALYSE-02-Tao-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-02-Tao-Lean-Python.ipynb) | ANALYSE-02 : Le manuel *Analysis I* de T. Tao en… | Python 3 | READY | BETA | 30min | po-2024 | +| 3 | [ANALYSE-03-PFR-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-03-PFR-Lean.ipynb) | ANALYSE-03 : La conjecture de Freiman-Ruzsa… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 4 | [ANALYSE-04-PFR-Primitives-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-04-PFR-Primitives-Python.ipynb) | ANALYSE-04 : Trois primitives de PFR, et l'endroit… | Python 3 | READY | BETA | 30min | po-2024 | +| 5 | [Geometry-01-From-Figure-To-Equation.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-01-From-Figure-To-Equation.ipynb) | Geometry 01 — De la figure à l'équation | Python 3 | READY | BETA | 30min | po-2024 | +| 6 | [Geometry-02-From-Equation-To-Proof.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-02-From-Equation-To-Proof.ipynb) | Geometry 02 — Prouver par l'algèbre | Python 3 | READY | BETA | 45min | po-2024 | +| 7 | [Geometry-03-Wu-Method-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-03-Wu-Method-Python.ipynb) | Geometry 03 — La méthode de Wu | Python 3 | READY | BETA | 45min | po-2024 | +| 8 | [Geometry-03b-Ritt-Decomposition-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-03b-Ritt-Decomposition-Python.ipynb) | Geometry 03b — Décomposition de Ritt et… | Python 3 (ipykernel) | READY | BETA | 45min | po-2024 | +| 9 | [Geometry-04-DD-AR-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-04-DD-AR-Python.ipynb) | Geometry 04 — Raisonner comme un géomètre (DD +… | Python 3 | READY | BETA | 30min | po-2024 | +| 10 | [01-formes-modulaires-sl2z-hecke.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Langlands/01-formes-modulaires-sl2z-hecke.ipynb) | Langlands 01 : formes modulaires — de SL₂(ℤ) aux… | Python 3 | READY | BETA | 30min | po-2024 | +| 11 | [02-monstrous-moonshine-invariant-j.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Langlands/02-monstrous-moonshine-invariant-j.ipynb) | Monstrous Moonshine : l'invariant $j$ et le… | Python 3 | READY | BETA | 30min | po-2024 | +| 12 | [Lean-01-Setup-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-01-Setup-Lean-Python.ipynb) | Lean 4 - Installation et Configuration | Python 3 | READY | BETA | 30min | po-2024 | +| 13 | [Lean-02-Dependent-Types-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-02-Dependent-Types-Lean.ipynb) | Lean 2 - Types Dependants et Calcul des… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 14 | [Lean-03-Propositions-Proofs-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-03-Propositions-Proofs-Lean.ipynb) | Lean 3 - Propositions et Preuves | Lean 4 | READY | BETA | 45min | po-2024 | +| 15 | [Lean-03b-Formalized-Formal-Logic-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-03b-Formalized-Formal-Logic-Lean-Python.ipynb) | Lean-3b — Formalized Formal Logic : le laboratoire… | Python 3 | READY | BETA | 30min | po-2024 | +| 16 | [Lean-04-Quantifiers-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-04-Quantifiers-Lean.ipynb) | Lean 4 - Quantificateurs et Logique du Premier… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 17 | [Lean-05-Tactics-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-05-Tactics-Lean.ipynb) | Lean 5 - Mode Tactique | Lean 4 | READY | BETA | 1h | po-2024 | +| 18 | [Lean-06-Mathlib-Essentials-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-06-Mathlib-Essentials-Lean.ipynb) | Lean 6 - Mathlib4 : La Bibliotheque Mathematique | Lean 4 | READY | BETA | 45min | po-2024 | +| 19 | [Lean-07-LLM-Integration-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-07-LLM-Integration-Lean-Python.ipynb) | Lean 7 - Integration des LLMs pour l'Assistance… | Python 3 (WSL) | READY | BETA | 45min | po-2024 | +| 20 | [Lean-07b-Examples-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-07b-Examples-Python.ipynb) | Lean 7b - Exemples Progressifs et Benchmarks | Python 3 (WSL) | READY | BETA | 30min | po-2024 | +| 21 | [Lean-08-Agentic-Proving-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-08-Agentic-Proving-Python.ipynb) | Lean-8 - Agents Autonomes pour Demonstration de… | Python 3 | READY | BETA | 30min | po-2024 | +| 22 | [Lean-08b-Erdos-Formal-Conjectures-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-08b-Erdos-Formal-Conjectures-Lean.ipynb) | Lean 8b : le programme Erdős et le pattern… | Lean 4 (WSL,… | READY | BETA | 30min | po-2024 | +| 23 | [Lean-09-SK-Multi-Agents-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-09-SK-Multi-Agents-Lean-Python.ipynb) | Lean 9 : Multi-Agents avec Semantic Kernel | Python 3.13.x (CPython… | READY | BETA | 45min | po-2024 | +| 24 | [Lean-10-LeanDojo.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-10-LeanDojo.ipynb) | Lean 10 : LeanDojo - ML/LLM Theorem Proving | Python 3 (WSL) | READY | BETA | 45min | po-2024 | +| 25 | [Lean-11-TorchLean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-11-TorchLean.ipynb) | Lean 11 - TorchLean : Réseaux de Neurones… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 26 | [Lean-11b-TorchLean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-11b-TorchLean-Python.ipynb) | Lean 11b - TorchLean : Implémentation Python des… | Python 3 | READY | BETA | 45min | po-2024 | +| 27 | [Lean-12-Sensitivity-Theorem.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12-Sensitivity-Theorem.ipynb) | Lean-12 : Le Théorème de Sensibilité (Huang 2019) | Python 3 | READY | BETA | 30min | po-2024 | +| 28 | [Lean-12b-Lean-Sensitivity-Theorem.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12b-Lean-Sensitivity-Theorem.ipynb) | Lean-12b — Théorème de Sensibilité de Huang… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 29 | [Lean-12c-Tensor-Product-Representations-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12c-Tensor-Product-Representations-Lean.ipynb) | Lean-12c : algèbre TPR — binding, unbinding et… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 30 | [Lean-13-Kochen-Specker.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13-Kochen-Specker.ipynb) | Lean-13 : Le Théorème de Kochen-Specker (Cabello… | Python 3 | READY | BETA | 30min | po-2024 | +| 31 | [Lean-13b-CHSH-Tsirelson-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13b-CHSH-Tsirelson-Native.ipynb) | Lean-13b : la borne de Tsirelson — digestion… | Lean 4 (WSL, conway-build) | READY | BETA | 30min | po-2024 | +| 32 | [Lean-13c-CHSH-Landau-Saturation.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13c-CHSH-Landau-Saturation.ipynb) | Lean-13c : la saturation de Tsirelson — le témoin… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 33 | [Lean-14-Finiteness-Derivatives.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-14-Finiteness-Derivatives.ipynb) | Lean-14 — Dérivées symboliques de Brzozowski : la… | Python 3 | READY | DRAFT | 15min | po-2024 | +| 34 | [Lean-14b-Finiteness-Lean-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-14b-Finiteness-Lean-Companion.ipynb) | Lean-14b - Finiteness des dérivées de Brzozowski —… | Lean 4 (WSL) | READY | DRAFT | 30min | po-2024 | +| 35 | [Lean-15-Grothendieck-Tribute.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15-Grothendieck-Tribute.ipynb) | Lean-15 : Hommage a Alexandre Grothendieck -- Le… | Python 3 | READY | BETA | 30min | po-2024 | +| 36 | [Lean-15b-Lean-Grothendieck.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15b-Lean-Grothendieck.ipynb) | Lean-15b : Grothendieck en Lean -- Atelier… | Python 3 | READY | BETA | 45min | po-2024 | +| 37 | [Lean-15c-Lean-Grothendieck-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15c-Lean-Grothendieck-Companion.ipynb) | Lean-15c : le lake Grothendieck par ses énoncés… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 38 | [Lean-15d-Lean-Grothendieck-Visuel-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15d-Lean-Grothendieck-Visuel-Python.ipynb) | Lean-15d : Grothendieck en images | Python 3 | READY | ALPHA | 30min | po-2024 | +| 39 | [Lean-16a-Conway-Man-and-Work.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16a-Conway-Man-and-Work.ipynb) | Lean-16a - Conway, l'homme et l'oeuvre | Python 3 (ipykernel) | READY | BETA | 45min | po-2024 | +| 40 | [Lean-16b-Conway-Game-of-Life-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16b-Conway-Game-of-Life-Lean.ipynb) | Lean-16b : Hommage a John Conway — Game of Life as… | Python 3 (ipykernel) | READY | BETA | 45min | po-2024 | +| 41 | [Lean-16c-Conway-Game-of-Life-Golly.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16c-Conway-Game-of-Life-Golly.ipynb) | Lean-16c - Conway Game of Life : les 3 piliers, en… | Python 3 | READY | BETA | 45min | po-2024 | +| 42 | [Lean-16d-Conway-Game-of-Life-Lean-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16d-Conway-Game-of-Life-Lean-Native.ipynb) | Lean-16d : Game of Life sur kernel Lean natif | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 43 | [Lean-16e-Conway-FRACTRAN-Lean-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16e-Conway-FRACTRAN-Lean-Native.ipynb) | Lean-16e : FRACTRAN, la machine universelle de… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 44 | [Lean-16f-Conway-Free-Will-Theorem.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16f-Conway-Free-Will-Theorem.ipynb) | Lean-16f : Le Théorème du Libre Arbitre… | Python 3 | READY | BETA | 45min | po-2024 | +| 45 | [Lean-16g-Conway-Canons.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16g-Conway-Canons.ipynb) | Lean 16g — Canons : le barreau 2 de l'échelle des… | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | +| 46 | [Lean-16h-Conway-PatternTour-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16h-Conway-PatternTour-Native.ipynb) | Lean-16h : la tournée des motifs du Jeu de la Vie… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 47 | [Lean-16i-Translateur-Life.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16i-Translateur-Life.ipynb) | Lean-16i — Synthèse d'un translateur minuscule :… | Python 3 | READY | BETA | 15min | po-2024 | +| 48 | [Lean-16j-Conway-Hashlife-Correctness-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16j-Conway-Hashlife-Correctness-Native.ipynb) | Lean-16j : la preuve de correction Hashlife —… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 49 | [Lean-17a-Knots-Conway-Proofs.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17a-Knots-Conway-Proofs.ipynb) | Lean 17a — Conway, les Nœuds et la Preuve de… | Python 3 | READY | BETA | 30min | po-2024 | +| 50 | [Lean-17b-Knots-Invariants-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17b-Knots-Invariants-Companion.ipynb) | Lean 17b — Invariants de Nœuds : Calcul et… | Python 3 | READY | BETA | 45min | po-2024 | +| 51 | [Lean-17c-Knots-Companion-Formel.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17c-Knots-Companion-Formel.ipynb) | Lean 17c — Le lake knot_lean par ses déclarations… | Python 3 | READY | BETA | 30min | po-2024 | +| 52 | [Lean-20-Capstone-Digestions-Tao-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-20-Capstone-Digestions-Tao-Python.ipynb) | Lean-20 : Capstone — digérer le travail formel de… | Python 3 | READY | BETA | 15min | po-2024 | +| 53 | [Lean-21-MIMO-Detection-Flips.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21-MIMO-Detection-Flips.ipynb) | Lean-21 : Detection MIMO par flips -- le seuil 2… | Python 3 | READY | BETA | 30min | po-2024 | +| 54 | [Lean-21b-MIMO-Converse-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21b-MIMO-Converse-Native.ipynb) | Lean-21b : le lake mimo_lean par ses énoncés —… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 55 | [Lean-21c-Descente-Budget.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21c-Descente-Budget.ipynb) | Lean-21c : Le budget de descente - quand la… | Python 3 | READY | BETA | 30min | po-2024 | +| 56 | [Lean-22-Galois-Probleme-Inverse-M23.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-22-Galois-Probleme-Inverse-M23.ipynb) | Lean-22 : Le problème inverse de Galois — M₂₃… | Python 3 | READY | BETA | 45min | po-2024 | +| 57 | [Lean-23-ERC20-Invariant-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-23-ERC20-Invariant-Companion.ipynb) | Lean-23 : ERC-20 sous Lean 4 — l'invariant de… | Python3 | READY | BETA | 15min | po-2024 | +| 58 | [Lean-23b-Lean-ERC20-Native-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-23b-Lean-ERC20-Native-Companion.ipynb) | Lean-23b — ERC-20 natif : l'invariant de… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 59 | [Lean-24-Calibration-Native-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-24-Calibration-Native-Companion.ipynb) | Lean-24 : le lake calibration_lean par ses énoncés… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 60 | [Lean-24b-Confiance-Preuves-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-24b-Confiance-Preuves-Native.ipynb) | Lean-24b : Confiance et preuves — quand un… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 61 | [Lean-25-Coherence-et-Temoin.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-25-Coherence-et-Temoin.ipynb) | Lean-25 — Cohérence et témoin : de Finetti… | Python 3 | READY | BETA | 30min | po-2024 | +| 62 | [Lean-26-Munkres-Tribute.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-26-Munkres-Tribute.ipynb) | Lean-26 : Hommage à James R. Munkres — le cours… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 63 | [Lean-27-EdgeColoring-Tutte-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-27-EdgeColoring-Tutte-Companion.ipynb) | Lean-27 : coloration d'arêtes et conjecture de… | Lean 4 (WSL) | READY | BETA | 15min | po-2024 | +| 64 | [Lean-28-Complex-Structure-S6.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-28-Complex-Structure-S6.ipynb) | Lean-28 : Le problème de Hopf sur S⁶ — digestion… | Python 3 | READY | BETA | 30min | po-2024 | +| 65 | [Lean-29-Hecke-Operators-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-29-Hecke-Operators-Native.ipynb) | Lean-29 : les opérateurs de Hecke $T_p$ et $U_p$ —… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 66 | [Lean-30-FormalGroups-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-30-FormalGroups-Native.ipynb) | Lean-30 : groupes formels multivariés — compagnon… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 67 | [Lean-31-Euler-Navier-Stokes.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-31-Euler-Navier-Stokes.ipynb) | Lean-31 : Euler et Navier–Stokes — reproduction… | Python 3 | READY | BETA | 45min | po-2024 | +| 68 | [Lean-33-Distribution-Spaces.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-33-Distribution-Spaces.ipynb) | Lean-33 : espaces de Schwartz — décroissance et… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 69 | [Lean-34-Calculabilite-et-Limites.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-34-Calculabilite-et-Limites.ipynb) | Lean-34 — Calculabilité et limites : de l'arrêt… | Python 3 | READY | BETA | 30min | po-2024 | +| 70 | [Lean-34b-FairBot-Loeb.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-34b-FairBot-Loeb.ipynb) | Lean-34b — FairBot par le théorème de Löb :… | Python 3 | READY | BETA | 30min | po-2024 | +| 71 | [Lean-36-Structures-Finies-MUH-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-36-Structures-Finies-MUH-Lean.ipynb) | Lean-36 : structures mathematiques finies —… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 72 | [Lean-37-Capstone-Serre100.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-37-Capstone-Serre100.ipynb) | Lean-37 : Capstone — la sous-série « Serre 100 » | Python 3 | READY | BETA | 15min | po-2024 | +| 73 | [01-corps-finis-borne-hasse.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/01-corps-finis-borne-hasse.ipynb) | Corps finis et la borne de Hasse — distiller un… | Python 3 | READY | BETA | 30min | po-2024 | +| 74 | [02-valeurs-zeta-multiples-finies.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/02-valeurs-zeta-multiples-finies.ipynb) | 2. Valeurs zêta multiples finies — l'anneau des… | Python 3 | READY | BETA | 30min | po-2024 | +| 75 | [03-cohomologie-cech-espaces-finis.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/03-cohomologie-cech-espaces-finis.ipynb) | Cohomologie de Čech calculée — espaces… | Python 3 | READY | BETA | 45min | po-2024 | +| 76 | [04-lemme-yoneda-categories-finies.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/04-lemme-yoneda-categories-finies.ipynb) | Lemme de Yoneda calculé — catégories finies | Python 3 | READY | BETA | 30min | po-2024 | +| 77 | [05-table-de-caracteres.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/05-table-de-caracteres.ipynb) | 5. Tables de caractères — le squelette… | Python 3 | READY | BETA | 45min | po-2024 | +| 78 | [06-bulles-minkowski.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/06-bulles-minkowski.ipynb) | Les bulles diaboliques de Minkowski — géométrie… | Python 3 | READY | BETA | 30min | po-2024 | +| 79 | [07-zeros-fonctions-l-gaps-gue.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/07-zeros-fonctions-l-gaps-gue.ipynb) | Zéros de fonctions L, gaps et statistique GUE | Python 3 | READY | BETA | 45min | po-2024 | +| 80 | [08-serre-dans-mathlib.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/08-serre-dans-mathlib.ipynb) | Serre dans Mathlib — tour guidé des cinq monuments | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 81 | [09-congruences-tau-lacunarite-delta.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/09-congruences-tau-lacunarite-delta.ipynb) | τ de Ramanujan — congruences, borne de Deligne, et… | Python 3 | READY | BETA | 30min | po-2024 | +| 82 | [10-empilements-borne-lp-cohn-elkies.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/10-empilements-borne-lp-cohn-elkies.ipynb) | 10 — Empilements de sphères : la borne linéaire de… | Python 3 | READY | BETA | 30min | po-2024 | #### Planners (25) @@ -886,7 +907,7 @@ Total notebooks: 1312 | 2 | [SW-1-CSharp-Setup.ipynb](MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-1-CSharp-Setup.ipynb) | SW-1-Setup | .NET (C#) | READY | BETA | 30min | po-2024 | | 3 | [SW-10-CSharp-RDFStar.ipynb](MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-10-CSharp-RDFStar.ipynb) | SW-10-CSharp-RDFStar — Jumeau C# : annoter des… | .NET (C#) | READY | BETA | 45min | po-2024 | | 4 | [SW-10-Python-RDFStar.ipynb](MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-10-Python-RDFStar.ipynb) | SW-10-Python-RDFStar | Python 3 | READY | BETA | 45min | po-2024 | -| 5 | [SW-11-CSharp-KnowledgeGraphs.ipynb](MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-11-CSharp-KnowledgeGraphs.ipynb) | SW-11-CSharp-KnowledgeGraphs | .NET (C#) | READY | BETA | 45min | po-2024 | +| 5 | [SW-11-CSharp-KnowledgeGraphs.ipynb](MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-11-CSharp-KnowledgeGraphs.ipynb) | SW-11-CSharp-KnowledgeGraphs | .NET (C#) | READY | ALPHA | 45min | po-2024 | | 6 | [SW-11-Python-KnowledgeGraphs.ipynb](MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-11-Python-KnowledgeGraphs.ipynb) | SW-11-Python-KnowledgeGraphs | Python 3 | READY | ALPHA | 1h | po-2024 | | 7 | [SW-12-Python-GraphRAG.ipynb](MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-12-Python-GraphRAG.ipynb) | SW-12-Python-GraphRAG | Python 3 | DEMO | BETA | 45min | po-2024 | | 8 | [SW-13-Python-Reasoners.ipynb](MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-13-Python-Reasoners.ipynb) | SW-13-Reasoners | Python 3 | READY | BETA | 1h | po-2024 | @@ -915,39 +936,39 @@ Total notebooks: 1312 | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| -| 1 | [SC-0-Cypherpunk-Origins.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-0-Cypherpunk-Origins.ipynb) | SC-0-Cypherpunk-Origins - Les origines Cypherpunk… | Python 3 | READY | BETA | 45min | po-2024 | -| 2 | [SC-1-Setup-Foundry.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-1-Setup-Foundry.ipynb) | SC-1-Setup-Foundry - Environnement Smart Contracts | Python 3 | READY | BETA | 15min | po-2024 | -| 3 | [SC-2-Setup-Web3py.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-2-Setup-Web3py.ipynb) | SC-2-Setup-Web3py - Python et la Blockchain | Python 3 | READY | BETA | 30min | po-2024 | -| 4 | [SC-2b-Bac-ASable-Institutionnel.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-2b-Bac-ASable-Institutionnel.ipynb) | SC-2b - Bac a sable institutionnel : des acteurs,… | Python 3 | READY | BETA | 45min | po-2024 | -| 5 | [SC-3-Solidity-Basics.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-3-Solidity-Basics.ipynb) | SC-3-Solidity-Basics - Fondements de Solidity | .venv | READY | BETA | 45min | po-2024 | -| 6 | [SC-4-Functions-State.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-4-Functions-State.ipynb) | SC-4-Functions-State - Fonctions et État | Python 3 | READY | BETA | 45min | po-2024 | -| 7 | [SC-5-Inheritance.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-5-Inheritance.ipynb) | SC-5-Inheritance - Heritage et Interfaces | Python 3 | READY | BETA | 30min | po-2024 | -| 8 | [SC-6-Errors-Events.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-6-Errors-Events.ipynb) | SC-6-Errors-Events - Erreurs et Événements | Python 3 | READY | BETA | 30min | po-2024 | -| 9 | [SC-10-Account-Abstraction.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-10-Account-Abstraction.ipynb) | SC-10-Account-Abstraction - ERC-4337 v0.9 | Python 3 | READY | BETA | 30min | po-2024 | -| 10 | [SC-11-LLM-Assisted.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-11-LLM-Assisted.ipynb) | SC-11-LLM-Assisted - Développement Smart Contracts… | Python 3 | READY | BETA | 45min | po-2024 | -| 11 | [SC-7-Token-Standards.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-7-Token-Standards.ipynb) | SC-7-Token-Standards - Standards de Tokens | Python 3 | READY | BETA | 30min | po-2024 | -| 12 | [SC-7b-ERC20-Lean-Verification-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-7b-ERC20-Lean-Verification-Companion.ipynb) | SC-7b : ERC-20 + Lean — vérification formelle de… | Python3 | READY | BETA | 15min | po-2024 | -| 13 | [SC-7c-ERC20-Lean-Native-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-7c-ERC20-Lean-Native-Companion.ipynb) | SC-7c : ERC-20 — compagnon natif Lean (kernel… | Lean 4 (WSL) | READY | ALPHA | 30min | po-2024 | -| 14 | [SC-8-DeFi-Primitives.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-8-DeFi-Primitives.ipynb) | SC-8-DeFi-Primitives - Primitives DeFi | Python 3 | READY | BETA | 30min | po-2024 | -| 15 | [SC-9-DAO-Governance.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-9-DAO-Governance.ipynb) | SC-9-DAO-Governance - Gouvernance DAO | cours-ia | READY | BETA | 30min | po-2024 | -| 16 | [SC-12-Foundry-Testing.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/03-Foundry-Testing/SC-12-Foundry-Testing.ipynb) | SC-12-Foundry-Testing - Tests avec Foundry | Python 3 | READY | BETA | 45min | po-2024 | -| 17 | [SC-13-Fuzz-Invariants.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/03-Foundry-Testing/SC-13-Fuzz-Invariants.ipynb) | SC-13-Fuzz-Invariants - Fuzz Testing | Python 3 | READY | BETA | 30min | po-2024 | -| 18 | [SC-14-Formal-Verification.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/03-Foundry-Testing/SC-14-Formal-Verification.ipynb) | SC-14-Formal-Vérification - Vérification Formelle | Python 3 | DEMO | BETA | 30min | po-2024 | -| 19 | [SC-15-Zero-Knowledge-Proofs.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-15-Zero-Knowledge-Proofs.ipynb) | SC-15-Zero-Knowledge-Proofs - Preuves a… | Python 3 | READY | BETA | 45min | po-2024 | -| 20 | [SC-16-Homomorphic-Encryption.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-16-Homomorphic-Encryption.ipynb) | SC-16-Homomorphic-Encryption - Chiffrement… | Python 3 (SC-16 Concrete, WSL) | READY | BETA | 30min | po-2024 | -| 21 | [SC-17-E2E-Verifiable-Voting.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-17-E2E-Verifiable-Voting.ipynb) | SC-17-E2E-Verifiable-Voting - Vote Electronique… | Python 3 | READY | BETA | 30min | po-2024 | -| 22 | [SC-18-Vyper.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-18-Vyper.ipynb) | SC-18-Vyper - Smart Contracts en Python-like | Python 3 | READY | BETA | 30min | po-2024 | -| 23 | [SC-19-Ripple-XRP.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-19-Ripple-XRP.ipynb) | SC-19-Ripple-XRP - Protocole Ripple et XRP Ledger | Python 3 (smartcontracts) | READY | BETA | 30min | po-2024 | -| 24 | [SC-20-Bitcoin-Scripting.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-20-Bitcoin-Scripting.ipynb) | SC-20-Bitcoin-Scripting - Bitcoin, UTXO et Scripts | .venv | READY | BETA | 30min | po-2024 | -| 25 | [SC-21-Move-Sui.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-21-Move-Sui.ipynb) | SC-21-Move-Sui - Move sur Sui | Python 3 | READY | BETA | 30min | po-2024 | -| 26 | [SC-22-Solana-Anchor.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-22-Solana-Anchor.ipynb) | SC-22-Solana-Anchor - Solana avec Anchor | Python 3 | READY | BETA | 30min | po-2024 | -| 27 | [SC-23-Cross-Chain.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/06-Real-World/SC-23-Cross-Chain.ipynb) | SC-23-Cross-Chain - Interoperabilite Cross-Chain | Python 3 | READY | BETA | 30min | po-2024 | -| 28 | [SC-24-Testnet-Deploy.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/06-Real-World/SC-24-Testnet-Deploy.ipynb) | SC-24 : Deploiement sur Testnets | Python 3 | READY | BETA | 30min | po-2024 | -| 29 | [SC-25-Mainnet-Deploy.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/06-Real-World/SC-25-Mainnet-Deploy.ipynb) | SC-25 : Deploiement Mainnet (L2) | Python 3 | READY | BETA | 30min | po-2024 | -| 30 | [SC-26-Final-Project.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/06-Real-World/SC-26-Final-Project.ipynb) | SC-26 : Projet Final - DApp Complete | Python 3 | READY | BETA | 15min | po-2024 | -| 31 | [SC-27-Dette-Irreversibilite.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/06-Real-World/SC-27-Dette-Irreversibilite.ipynb) | SC-27 : Dette d'irréversibilité — la boucle de… | Python 3 | READY | BETA | 30min | po-2024 | - -#### SMT (46) +| 1 | [SC-00-Cypherpunk-Origins-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-00-Cypherpunk-Origins-Python.ipynb) | SC-00-Cypherpunk-Origins-Python - Les origines… | Python 3 | READY | BETA | 45min | po-2024 | +| 2 | [SC-01-Setup-Foundry-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-01-Setup-Foundry-Python.ipynb) | SC-01-Setup-Foundry-Python - Environnement Smart… | Python 3 | READY | BETA | 15min | po-2024 | +| 3 | [SC-02-Setup-Web3py-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-02-Setup-Web3py-Python.ipynb) | SC-02-Setup-Web3py-Python - Python et la… | Python 3 | READY | BETA | 30min | po-2024 | +| 4 | [SC-02b-Bac-ASable-Institutionnel-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-02b-Bac-ASable-Institutionnel-Python.ipynb) | SC-2b - Bac a sable institutionnel : des acteurs,… | Python 3 | READY | BETA | 45min | po-2024 | +| 5 | [SC-03-Solidity-Basics-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-03-Solidity-Basics-Python.ipynb) | SC-03-Solidity-Basics-Python - Fondements de… | .venv | READY | BETA | 45min | po-2024 | +| 6 | [SC-04-Functions-State-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-04-Functions-State-Python.ipynb) | SC-04-Functions-State-Python - Fonctions et État | Python 3 | READY | BETA | 45min | po-2024 | +| 7 | [SC-05-Inheritance-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-05-Inheritance-Python.ipynb) | SC-05-Inheritance-Python - Heritage et Interfaces | Python 3 | READY | BETA | 30min | po-2024 | +| 8 | [SC-06-Errors-Events-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-06-Errors-Events-Python.ipynb) | SC-06-Errors-Events-Python - Erreurs et Événements | Python 3 | READY | BETA | 30min | po-2024 | +| 9 | [SC-07-Token-Standards-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-07-Token-Standards-Python.ipynb) | SC-07-Token-Standards-Python - Standards de Tokens | Python 3 | READY | BETA | 30min | po-2024 | +| 10 | [SC-07c-ERC20-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-07c-ERC20-Lean.ipynb) | SC-7c : ERC-20 — compagnon natif Lean (kernel… | Lean 4 (WSL) | READY | ALPHA | 30min | po-2024 | +| 11 | [SC-08-DeFi-Primitives-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-08-DeFi-Primitives-Python.ipynb) | SC-08-DeFi-Primitives-Python - Primitives DeFi | Python 3 | READY | BETA | 30min | po-2024 | +| 12 | [SC-09-DAO-Governance-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-09-DAO-Governance-Python.ipynb) | SC-09-DAO-Governance-Python - Gouvernance DAO | cours-ia | READY | BETA | 30min | po-2024 | +| 13 | [SC-10-Account-Abstraction-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-10-Account-Abstraction-Python.ipynb) | SC-10-Account-Abstraction-Python - ERC-4337 v0.9 | Python 3 | READY | BETA | 30min | po-2024 | +| 14 | [SC-11-LLM-Assisted-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-11-LLM-Assisted-Python.ipynb) | SC-11-LLM-Assisted-Python - Développement Smart… | Python 3 | READY | BETA | 45min | po-2024 | +| 15 | [SC-7b-ERC20-Lean-Verification-Companion.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-7b-ERC20-Lean-Verification-Companion.ipynb) | SC-7b : ERC-20 + Lean — vérification formelle de… | Python3 | READY | BETA | 15min | po-2024 | +| 16 | [SC-12-Foundry-Testing-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/03-Foundry-Testing/SC-12-Foundry-Testing-Python.ipynb) | SC-12-Foundry-Testing-Python - Tests avec Foundry | Python 3 | READY | BETA | 45min | po-2024 | +| 17 | [SC-13-Fuzz-Invariants-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/03-Foundry-Testing/SC-13-Fuzz-Invariants-Python.ipynb) | SC-13-Fuzz-Invariants-Python - Fuzz Testing | Python 3 | READY | BETA | 30min | po-2024 | +| 18 | [SC-14-Formal-Verification-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/03-Foundry-Testing/SC-14-Formal-Verification-Python.ipynb) | SC-14-Formal-Vérification - Vérification Formelle | Python 3 | DEMO | BETA | 30min | po-2024 | +| 19 | [SC-15-Zero-Knowledge-Proofs-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-15-Zero-Knowledge-Proofs-Python.ipynb) | SC-15-Zero-Knowledge-Proofs-Python - Preuves a… | Python 3 | READY | BETA | 45min | po-2024 | +| 20 | [SC-16-Homomorphic-Encryption-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-16-Homomorphic-Encryption-Python.ipynb) | SC-16-Homomorphic-Encryption-Python - Chiffrement… | Python 3 (SC-16 Concrete, WSL) | READY | BETA | 30min | po-2024 | +| 21 | [SC-17-E2E-Verifiable-Voting-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-17-E2E-Verifiable-Voting-Python.ipynb) | SC-17-E2E-Verifiable-Voting-Python - Vote… | Python 3 | READY | BETA | 30min | po-2024 | +| 22 | [SC-18-Vyper-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-18-Vyper-Python.ipynb) | SC-18-Vyper-Python - Smart Contracts en… | Python 3 | READY | BETA | 30min | po-2024 | +| 23 | [SC-19-Ripple-XRP-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-19-Ripple-XRP-Python.ipynb) | SC-19-Ripple-XRP-Python - Protocole Ripple et XRP… | Python 3 (smartcontracts) | READY | BETA | 30min | po-2024 | +| 24 | [SC-20-Bitcoin-Scripting-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-20-Bitcoin-Scripting-Python.ipynb) | SC-20-Bitcoin-Scripting-Python - Bitcoin, UTXO et… | .venv | READY | BETA | 30min | po-2024 | +| 25 | [SC-21-Move-Sui-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-21-Move-Sui-Python.ipynb) | SC-21-Move-Sui-Python - Move sur Sui | Python 3 | READY | BETA | 30min | po-2024 | +| 26 | [SC-22-Solana-Anchor-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-22-Solana-Anchor-Python.ipynb) | SC-22-Solana-Anchor-Python - Solana avec Anchor | Python 3 | READY | BETA | 30min | po-2024 | +| 27 | [SC-23-Cross-Chain-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/06-Real-World/SC-23-Cross-Chain-Python.ipynb) | SC-23-Cross-Chain-Python - Interoperabilite… | Python 3 | READY | BETA | 30min | po-2024 | +| 28 | [SC-24-Testnet-Deploy-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/06-Real-World/SC-24-Testnet-Deploy-Python.ipynb) | SC-24 : Deploiement sur Testnets | Python 3 | READY | BETA | 30min | po-2024 | +| 29 | [SC-25-Mainnet-Deploy-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/06-Real-World/SC-25-Mainnet-Deploy-Python.ipynb) | SC-25 : Deploiement Mainnet (L2) | Python 3 | READY | BETA | 30min | po-2024 | +| 30 | [SC-26-Final-Project-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/06-Real-World/SC-26-Final-Project-Python.ipynb) | SC-26 : Projet Final - DApp Complete | Python 3 | READY | BETA | 15min | po-2024 | +| 31 | [SC-27-Dette-Irreversibilite-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/06-Real-World/SC-27-Dette-Irreversibilite-Python.ipynb) | SC-27 : Dette d'irréversibilité — la boucle de… | Python 3 | READY | BETA | 30min | po-2024 | + +#### SMT (47) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -969,36 +990,37 @@ Total notebooks: 1312 | 16 | [Z3-10-Cryptarithmetic-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-10-Cryptarithmetic-Python.ipynb) | 10. Cryptarithmes (SEND + MORE = MONEY) | Python 3 | READY | BETA | 15min | po-2024 | | 17 | [Z3-11-Graph-Coloring-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-11-Graph-Coloring-Python.ipynb) | 11 - Coloration de Graphe avec Z3 | Python 3 | READY | BETA | 30min | po-2024 | | 18 | [Z3-12-Real-Arithmetic-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-12-Real-Arithmetic-Python.ipynb) | 12. Arithmetique reelle : raisonner sur les… | Python 3 | READY | BETA | 30min | po-2024 | -| 19 | [Z3-14-BitVectors-Overflow-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-14-BitVectors-Overflow-Python.ipynb) | 14. Bit-vectors : verifier le debordement… | Python 3 | READY | BETA | 30min | po-2024 | -| 20 | [Z3-15-Nested-Arrays-2D-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-15-Nested-Arrays-2D-Python.ipynb) | 15. Tableaux imbriqués et grilles 2D : carrés… | Python 3 | READY | BETA | 30min | po-2024 | -| 21 | [Z3-16-Meal-Planner-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16-Meal-Planner-Python.ipynb) | 16. Meal-Planner déclaratif : du modèle Z3 au plan… | Python 3 | READY | BETA | 30min | po-2024 | -| 22 | [Z3-16b-Meal-Planner-Data-External-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16b-Meal-Planner-Data-External-Python.ipynb) | Z3-Python-16b — Meal-Planner : couche de données… | Python 3 | READY | BETA | 30min | po-2024 | -| 23 | [Z3-16c-Meal-Planner-Patient-Capstone-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16c-Meal-Planner-Patient-Capstone-Python.ipynb) | Z3-Python-16c — Meal-Planner : capstone patient… | Python 3 | READY | BETA | 30min | po-2024 | -| 24 | [Z3-16d-Meal-Planner-Convergence-Scale-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16d-Meal-Planner-Convergence-Scale-Python.ipynb) | Z3-Python-16d — Convergence à l'échelle :… | Python 3 | READY | BETA | 30min | po-2024 | -| 25 | [Z3-16e-Meal-Planner-Optimize-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16e-Meal-Planner-Optimize-Python.ipynb) | Z3-Python-16e — Meal-Planner : l'optimisation (du… | Python 3 | READY | BETA | 30min | po-2024 | -| 26 | [Z3-17-Array-Theory-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-17-Array-Theory-Python.ipynb) | Z3-Python 17 — Théorie des tableaux : Select,… | Python 3 | READY | BETA | 15min | po-2024 | -| 27 | [Z3-18-Sudoku-Modes-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-18-Sudoku-Modes-Python.ipynb) | Z3-Python 18 — Sudoku 4x4 : comparaison des modes… | Python 3 | READY | BETA | 15min | po-2024 | -| 28 | [Z3-Python-13-UnsatCores.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-Python-13-UnsatCores.ipynb) | 13. UNSAT cores : expliquer l'insatisfiabilite (le… | Python 3 | READY | BETA | 30min | po-2024 | -| 29 | [01_Linq2Z3_Intro.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/01_Linq2Z3_Intro.ipynb) | LINQ to Z3 - Résolution de Contraintes Déclarative | .NET (C#) | READY | BETA | 45min | po-2024 | -| 30 | [02_Sudoku_Theorem_vs_Array.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/02_Sudoku_Theorem_vs_Array.ipynb) | Sudoku : Théorème Explicite vs Modèle Implicite… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 31 | [03_Sudoku_Modes_Comparison.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/03_Sudoku_Modes_Comparison.ipynb) | Sudoku 4x4 : comparaison des modes Array et… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 32 | [04_Array_Theory.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/04_Array_Theory.ipynb) | Théorie des Tableaux Z3 — Select, Store et… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 33 | [05_Nested_Arrays_2D.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/05_Nested_Arrays_2D.ipynb) | Tableaux Imbriqués et Grilles 2D : API Déclarative… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 34 | [06_Meal_Planner_Modelisation.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/06_Meal_Planner_Modelisation.ipynb) | Notebook 06 — Meal-Planner declaratif : du modèle… | .NET (C#) | READY | BETA | 1h | po-2024 | -| 35 | [07_Meal_Planner_Data_External.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/07_Meal_Planner_Data_External.ipynb) | 07 — Données réelles & externe : Ciqual × RecipeML… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 36 | [08_Meal_Planner_Patient_Capstone.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/08_Meal_Planner_Patient_Capstone.ipynb) | 08 — Capstone hiérarchique : du squelette int\[\]\[\]… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 37 | [09_Meal_Planner_Convergence_Scale.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/09_Meal_Planner_Convergence_Scale.ipynb) | 09 — Convergence à l'échelle : l'encodage décide… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 38 | [10_Witness_Generation_Automata.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/10_Witness_Generation_Automata.ipynb) | 10 — Générer un témoin depuis A & ~B (fork… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 39 | [11_Job_Shop_Scheduling.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/11_Job_Shop_Scheduling.ipynb) | Notebook 11 — Ordonnancement d'atelier (Job Shop… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 40 | [12_Graph_Coloring_Petersen.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/12_Graph_Coloring_Petersen.ipynb) | Notebook 12 - Coloration de graphe : le graphe de… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 41 | [13_Cryptarithmetic_SMT.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/13_Cryptarithmetic_SMT.ipynb) | Notebook 13 — Cryptarithmes : l'arithmétique… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 42 | [14_Optimize_MaxSAT.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/14_Optimize_MaxSAT.ipynb) | Notebook 14 — De SAT à OPT : optimisation et… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 43 | [15_BitVectors_Overflow.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/15_BitVectors_Overflow.ipynb) | 15 — Théorie des bit-vectors Z3 : vérifier le… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 44 | [16_RealArithmetic.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/16_RealArithmetic.ipynb) | 16 — Arithmétique réelle Z3 : raisonner sur les… | .NET (C#) | READY | DRAFT | 30min | po-2024 | -| 45 | [17_UnsatCores.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/17_UnsatCores.ipynb) | 17 — UNSAT cores Z3 : expliquer l'insatisfiabilité… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 46 | [18_Einsteins_Riddle.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/18_Einsteins_Riddle.ipynb) | Notebook 18 - L'enigme d'Einstein : la logique des… | .NET (C#) | READY | BETA | 30min | po-2024 | - -#### SymbolicLearning (26) +| 19 | [Z3-13-UnsatCores-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-13-UnsatCores-Python.ipynb) | 13. UNSAT cores : expliquer l'insatisfiabilite (le… | Python 3 | READY | BETA | 30min | po-2024 | +| 20 | [Z3-13b-UnsatCores-MUS-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-13b-UnsatCores-MUS-Python.ipynb) | Z3-Python-13b — UNSAT cores : le MUS… | Python 3 | READY | BETA | 15min | po-2024 | +| 21 | [Z3-14-BitVectors-Overflow-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-14-BitVectors-Overflow-Python.ipynb) | 14. Bit-vectors : verifier le debordement… | Python 3 | READY | BETA | 30min | po-2024 | +| 22 | [Z3-15-Nested-Arrays-2D-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-15-Nested-Arrays-2D-Python.ipynb) | 15. Tableaux imbriqués et grilles 2D : carrés… | Python 3 | READY | BETA | 30min | po-2024 | +| 23 | [Z3-16-Meal-Planner-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16-Meal-Planner-Python.ipynb) | 16. Meal-Planner déclaratif : du modèle Z3 au plan… | Python 3 | READY | BETA | 30min | po-2024 | +| 24 | [Z3-16b-Meal-Planner-Data-External-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16b-Meal-Planner-Data-External-Python.ipynb) | Z3-Python-16b — Meal-Planner : couche de données… | Python 3 | READY | BETA | 30min | po-2024 | +| 25 | [Z3-16c-Meal-Planner-Patient-Capstone-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16c-Meal-Planner-Patient-Capstone-Python.ipynb) | Z3-Python-16c — Meal-Planner : capstone patient… | Python 3 | READY | BETA | 30min | po-2024 | +| 26 | [Z3-16d-Meal-Planner-Convergence-Scale-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16d-Meal-Planner-Convergence-Scale-Python.ipynb) | Z3-Python-16d — Convergence à l'échelle :… | Python 3 | READY | BETA | 30min | po-2024 | +| 27 | [Z3-16e-Meal-Planner-Optimize-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16e-Meal-Planner-Optimize-Python.ipynb) | Z3-Python-16e — Meal-Planner : l'optimisation (du… | Python 3 | READY | BETA | 30min | po-2024 | +| 28 | [Z3-17-Array-Theory-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-17-Array-Theory-Python.ipynb) | Z3-Python 17 — Théorie des tableaux : Select,… | Python 3 | READY | BETA | 15min | po-2024 | +| 29 | [Z3-18-Sudoku-Modes-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-18-Sudoku-Modes-Python.ipynb) | Z3-Python 18 — Sudoku 4x4 : comparaison des modes… | Python 3 | READY | BETA | 15min | po-2024 | +| 30 | [01_Linq2Z3_Intro.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/01_Linq2Z3_Intro.ipynb) | LINQ to Z3 - Résolution de Contraintes Déclarative | .NET (C#) | READY | BETA | 45min | po-2024 | +| 31 | [02_Sudoku_Theorem_vs_Array.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/02_Sudoku_Theorem_vs_Array.ipynb) | Sudoku : Théorème Explicite vs Modèle Implicite… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 32 | [03_Sudoku_Modes_Comparison.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/03_Sudoku_Modes_Comparison.ipynb) | Sudoku 4x4 : comparaison des modes Array et… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 33 | [04_Array_Theory.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/04_Array_Theory.ipynb) | Théorie des Tableaux Z3 — Select, Store et… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 34 | [05_Nested_Arrays_2D.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/05_Nested_Arrays_2D.ipynb) | Tableaux Imbriqués et Grilles 2D : API Déclarative… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 35 | [06_Meal_Planner_Modelisation.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/06_Meal_Planner_Modelisation.ipynb) | Notebook 06 — Meal-Planner declaratif : du modèle… | .NET (C#) | READY | BETA | 1h | po-2024 | +| 36 | [07_Meal_Planner_Data_External.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/07_Meal_Planner_Data_External.ipynb) | 07 — Données réelles & externe : Ciqual × RecipeML… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 37 | [08_Meal_Planner_Patient_Capstone.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/08_Meal_Planner_Patient_Capstone.ipynb) | 08 — Capstone hiérarchique : du squelette int\[\]\[\]… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 38 | [09_Meal_Planner_Convergence_Scale.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/09_Meal_Planner_Convergence_Scale.ipynb) | 09 — Convergence à l'échelle : l'encodage décide… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 39 | [10_Witness_Generation_Automata.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/10_Witness_Generation_Automata.ipynb) | 10 — Générer un témoin depuis A & ~B (fork… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 40 | [11_Job_Shop_Scheduling.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/11_Job_Shop_Scheduling.ipynb) | Notebook 11 — Ordonnancement d'atelier (Job Shop… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 41 | [12_Graph_Coloring_Petersen.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/12_Graph_Coloring_Petersen.ipynb) | Notebook 12 - Coloration de graphe : le graphe de… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 42 | [13_Cryptarithmetic_SMT.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/13_Cryptarithmetic_SMT.ipynb) | Notebook 13 — Cryptarithmes : l'arithmétique… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 43 | [14_Optimize_MaxSAT.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/14_Optimize_MaxSAT.ipynb) | Notebook 14 — De SAT à OPT : optimisation et… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 44 | [15_BitVectors_Overflow.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/15_BitVectors_Overflow.ipynb) | 15 — Théorie des bit-vectors Z3 : vérifier le… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 45 | [16_RealArithmetic.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/16_RealArithmetic.ipynb) | 16 — Arithmétique réelle Z3 : raisonner sur les… | .NET (C#) | READY | DRAFT | 30min | po-2024 | +| 46 | [17_UnsatCores.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/17_UnsatCores.ipynb) | 17 — UNSAT cores Z3 : expliquer l'insatisfiabilité… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 47 | [18_Einsteins_Riddle.ipynb](MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/18_Einsteins_Riddle.ipynb) | Notebook 18 - L'enigme d'Einstein : la logique des… | .NET (C#) | READY | BETA | 30min | po-2024 | + +#### SymbolicLearning (27) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -1011,23 +1033,24 @@ Total notebooks: 1312 | 7 | [SL-12b-PavlovDLS-Reproduction.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-12b-PavlovDLS-Reproduction.ipynb) | SL-12b-PavlovDLS-Reproduction — artefact Pavlov… | Python 3 | READY | BETA | 30min | po-2024 | | 8 | [SL-12b-SpectralLogicSynthesis.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-12b-SpectralLogicSynthesis.ipynb) | SL-12b : Synthèse logique spectrale — Fourier… | Python 3 | READY | BETA | 45min | po-2024 | | 9 | [SL-13-Discover-TPR.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-13-Discover-TPR.ipynb) | SL-13 : DISCOVER léger — diagnostic de structure… | Python 3 | READY | BETA | 30min | po-2024 | -| 10 | [SL-14-AIFeynman-Discover-Equations.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-14-AIFeynman-Discover-Equations.ipynb) | SL-14 — AI Feynman : découvrir des équations | Python 3 | READY | BETA | 30min | po-2024 | -| 11 | [SL-15-LearnedConjectures-Solver.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-15-LearnedConjectures-Solver.ipynb) | SL-15 — Conjectures apprises pour un vérificateur… | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | -| 12 | [SL-1b-LogicalLearning-Lean-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-1b-LogicalLearning-Lean-Native.ipynb) | SL-1b — Apprentissage PAC formellement : le lake… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 13 | [SL-2-KnowledgeBasedLearning-Csharp.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-2-KnowledgeBasedLearning-Csharp.ipynb) | SL-2 - Apprentissage et Connaissance : EBL & RBL… | .NET (C#) | READY | ALPHA | 45min | po-2024 | -| 14 | [SL-2-KnowledgeBasedLearning.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-2-KnowledgeBasedLearning.ipynb) | SL-2 --- Apprentissage et Connaissance (EBL & RBL) | Python 3 | READY | BETA | 45min | po-2024 | -| 15 | [SL-3-RelevanceLearning-Csharp.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-3-RelevanceLearning-Csharp.ipynb) | SL-3 — Apprentissage basé sur la pertinence (twin… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 16 | [SL-3-RelevanceLearning.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-3-RelevanceLearning.ipynb) | SL-3 --- Apprentissage Base sur la Pertinence (RBL… | Python 3 | READY | BETA | 45min | po-2024 | -| 17 | [SL-4-InductiveLogicProgramming-Csharp.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-4-InductiveLogicProgramming-Csharp.ipynb) | SL-4 — Programmation Logique Inductive (ILP) —… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 18 | [SL-4-InductiveLogicProgramming.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-4-InductiveLogicProgramming.ipynb) | SL-4 --- Programmation Logique Inductive (ILP) | Python 3 (WSL) | READY | BETA | 45min | po-2024 | -| 19 | [SL-5-InverseResolution-Csharp.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-5-InverseResolution-Csharp.ipynb) | SL-5 - Resolution Inverse & ILP (C#) | .NET (C#) | READY | ALPHA | 45min | po-2024 | -| 20 | [SL-5-InverseResolution.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-5-InverseResolution.ipynb) | SL-5 --- Resolution Inverse et Progol (ILP… | Python 3 | READY | BETA | 30min | po-2024 | -| 21 | [SL-6-ModernILP-Csharp.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-6-ModernILP-Csharp.ipynb) | SL-6 (C#) : Moteurs ILP modernes — apprendre des… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 22 | [SL-6-ModernILP.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-6-ModernILP.ipynb) | SL-6 --- Moteurs ILP modernes : Aleph, Metagol,… | Python 3 (WSL) | READY | BETA | 30min | po-2024 | -| 23 | [SL-7-NeuroSymbolic.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-7-NeuroSymbolic.ipynb) | SL-7 : Integration Neuro-Symbolique | Python 3 | READY | BETA | 45min | po-2024 | -| 24 | [SL-8-KnowledgeGraphs-ILP-Csharp.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-8-KnowledgeGraphs-ILP-Csharp.ipynb) | SL-8 (C#) : ILP Moderne et Knowledge Graphs | .NET (C#) | READY | BETA | 45min | po-2024 | -| 25 | [SL-8-KnowledgeGraphs-ILP.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-8-KnowledgeGraphs-ILP.ipynb) | SL-8 - ILP Moderne et Knowledge Graphs | Python 3 | READY | BETA | 45min | po-2024 | -| 26 | [SL-9-LLM-SymbolicLearning.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-9-LLM-SymbolicLearning.ipynb) | SL-9 - LLMs et Apprentissage Symbolique :… | Python 3 | READY | BETA | 45min | po-2024 | +| 10 | [SL-13b-TPR-SAE.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-13b-TPR-SAE.ipynb) | SL-13b : TPR x SAE — deux lectures des mêmes états… | Python 3 | READY | BETA | 30min | po-2024 | +| 11 | [SL-14-AIFeynman-Discover-Equations.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-14-AIFeynman-Discover-Equations.ipynb) | SL-14 — AI Feynman : découvrir des équations | Python 3 | READY | BETA | 30min | po-2024 | +| 12 | [SL-15-LearnedConjectures-Solver.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-15-LearnedConjectures-Solver.ipynb) | SL-15 — Conjectures apprises pour un vérificateur… | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | +| 13 | [SL-1b-LogicalLearning-Lean-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-1b-LogicalLearning-Lean-Native.ipynb) | SL-1b — Apprentissage PAC formellement : le lake… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 14 | [SL-2-KnowledgeBasedLearning-Csharp.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-2-KnowledgeBasedLearning-Csharp.ipynb) | SL-2 - Apprentissage et Connaissance : EBL & RBL… | .NET (C#) | READY | ALPHA | 45min | po-2024 | +| 15 | [SL-2-KnowledgeBasedLearning.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-2-KnowledgeBasedLearning.ipynb) | SL-2 --- Apprentissage et Connaissance (EBL & RBL) | Python 3 | READY | BETA | 45min | po-2024 | +| 16 | [SL-3-RelevanceLearning-Csharp.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-3-RelevanceLearning-Csharp.ipynb) | SL-3 — Apprentissage basé sur la pertinence (twin… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 17 | [SL-3-RelevanceLearning.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-3-RelevanceLearning.ipynb) | SL-3 --- Apprentissage Base sur la Pertinence (RBL… | Python 3 | READY | BETA | 45min | po-2024 | +| 18 | [SL-4-InductiveLogicProgramming-Csharp.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-4-InductiveLogicProgramming-Csharp.ipynb) | SL-4 — Programmation Logique Inductive (ILP) —… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 19 | [SL-4-InductiveLogicProgramming.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-4-InductiveLogicProgramming.ipynb) | SL-4 --- Programmation Logique Inductive (ILP) | Python 3 (WSL) | READY | BETA | 45min | po-2024 | +| 20 | [SL-5-InverseResolution-Csharp.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-5-InverseResolution-Csharp.ipynb) | SL-5 - Resolution Inverse & ILP (C#) | .NET (C#) | READY | ALPHA | 45min | po-2024 | +| 21 | [SL-5-InverseResolution.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-5-InverseResolution.ipynb) | SL-5 --- Resolution Inverse et Progol (ILP… | Python 3 | READY | BETA | 30min | po-2024 | +| 22 | [SL-6-ModernILP-Csharp.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-6-ModernILP-Csharp.ipynb) | SL-6 (C#) : Moteurs ILP modernes — apprendre des… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 23 | [SL-6-ModernILP.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-6-ModernILP.ipynb) | SL-6 --- Moteurs ILP modernes : Aleph, Metagol,… | Python 3 (WSL) | READY | BETA | 30min | po-2024 | +| 24 | [SL-7-NeuroSymbolic.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-7-NeuroSymbolic.ipynb) | SL-7 : Integration Neuro-Symbolique | Python 3 | READY | BETA | 45min | po-2024 | +| 25 | [SL-8-KnowledgeGraphs-ILP-Csharp.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-8-KnowledgeGraphs-ILP-Csharp.ipynb) | SL-8 (C#) : ILP Moderne et Knowledge Graphs | .NET (C#) | READY | BETA | 45min | po-2024 | +| 26 | [SL-8-KnowledgeGraphs-ILP.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-8-KnowledgeGraphs-ILP.ipynb) | SL-8 - ILP Moderne et Knowledge Graphs | Python 3 | READY | BETA | 45min | po-2024 | +| 27 | [SL-9-LLM-SymbolicLearning.ipynb](MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-9-LLM-SymbolicLearning.ipynb) | SL-9 - LLMs et Apprentissage Symbolique :… | Python 3 | READY | BETA | 45min | po-2024 | #### Tweety (39) @@ -1073,7 +1096,7 @@ Total notebooks: 1312 | 38 | [Tweety-5e-Propositional-Lab-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Tweety/Tweety-5e-Propositional-Lab-Lean.ipynb) | Tweety-5e — Laboratoire propositionnel : validité,… | Python 3 | READY | BETA | 30min | po-2024 | | 39 | [Tweety-IKVM-Init-Probe.ipynb](MyIA.AI.Notebooks/SymbolicAI/Tweety/_probes/Tweety-IKVM-Init-Probe.ipynb) | Tweety .NET - Probe Phase 1 axe 2 : initialisation… | .NET (C#) | READY | BETA | 30min | po-2024 | -### QuantConnect (115 notebooks) — DEMO:44, READY:71 | ALPHA:12, BETA:65, DRAFT:37, TEMPLATE:1 +### QuantConnect (115 notebooks) — DEMO:44, READY:71 | ALPHA:12, BETA:64, DRAFT:38, TEMPLATE:1 #### kelly_lean (2) @@ -1163,7 +1186,7 @@ Total notebooks: 1312 | 12 | [QC-Py-10-Risk-Portfolio-Management.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-10-Risk-Portfolio-Management.ipynb) | Objectifs d'Apprentissage | Python 3 | DEMO | DRAFT | 1h | po-2026 | | 13 | [QC-Py-11-Technical-Indicators.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-11-Technical-Indicators.ipynb) | QC-Py-11 - Indicateurs Techniques dans… | Python 3 | DEMO | DRAFT | 45min | po-2026 | | 14 | [QC-Py-12-Backtesting-Analysis.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-12-Backtesting-Analysis.ipynb) | QC-Py-12 - Backtesting et Analyse de Performance | Python 3 | DEMO | DRAFT | 1h30 | po-2026 | -| 15 | [QC-Py-12b-Backtest-Validity.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-12b-Backtest-Validity.ipynb) | QC-Py-12b - Validité du backtest et signification… | Python 3 | READY | BETA | 30min | po-2026 | +| 15 | [QC-Py-12b-Backtest-Validity.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-12b-Backtest-Validity.ipynb) | QC-Py-12b - Validité du backtest et signification… | Python 3 | READY | DRAFT | 45min | po-2026 | | 16 | [QC-Py-13-Alpha-Models.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-13-Alpha-Models.ipynb) | QC-Py-13 - Alpha Models et Algorithm Framework | Python 3 | DEMO | DRAFT | 1h | po-2026 | | 17 | [QC-Py-14-Portfolio-Construction-Execution.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-14-Portfolio-Construction-Execution.ipynb) | QC-Py-14 - Portfolio Construction et Exécution… | Python 3 | DEMO | DRAFT | 1h | po-2026 | | 18 | [QC-Py-14b-Liquidity-Execution-Costs.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-14b-Liquidity-Execution-Costs.ipynb) | QC-Py-14b - Liquidité et coûts d'exécution : ce… | Python 3 | DEMO | BETA | 45min | po-2026 | @@ -1210,111 +1233,111 @@ Total notebooks: 1312 | 59 | [QC-Py-Cloud-14-DualMomentum.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-14-DualMomentum.ipynb) | QC-Py-Cloud-14 — Dual Momentum : Asset Sélection… | Python 3 | READY | BETA | 15min | po-2026 | | 60 | [QC-Py-Dataset-Workflow.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Dataset-Workflow.ipynb) | Workflow : Téléchargement et gestion des datasets | Python 3 | READY | ALPHA | 45min | po-2026 | -### GameTheory (109 notebooks) — BROKEN:1, DEMO:1, READY:107 | ALPHA:4, BETA:100, DRAFT:5 +### GameTheory (109 notebooks) — DEMO:1, READY:108 | ALPHA:5, BETA:100, DRAFT:4 #### Racine (99) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| -| 1 | [GameTheory-01-Setup.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-01-Setup.ipynb) | GameTheory-01-Setup | Python 3 | READY | BETA | 45min | po-2024 | -| 2 | [GameTheory-02-NormalForm-Csharp-Part2.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm-Csharp-Part2.ipynb) | GameTheory-2 (Part 2) : Support Enumeration —… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 3 | [GameTheory-02-NormalForm-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm-Csharp.ipynb) | GameTheory-2 : Jeux sous forme normale (C# / .NET)… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 1 | [GameTheory-01-Setup-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-01-Setup-Python.ipynb) | GameTheory-01-Setup-Python | Python 3 | READY | BETA | 45min | po-2024 | +| 2 | [GameTheory-02-NormalForm-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm-CSharp.ipynb) | GameTheory-2 : Jeux sous forme normale (C# / .NET)… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 3 | [GameTheory-02-NormalForm-Part2-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm-Part2-CSharp.ipynb) | GameTheory-2 (Part 2) : Support Enumeration —… | .NET (C#) | READY | BETA | 45min | po-2024 | | 4 | [GameTheory-02-NormalForm-Part2-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm-Part2-Python.ipynb) | GameTheory-2 (Part 2) : Support Enumeration —… | Python 3 | READY | BETA | 30min | po-2024 | -| 5 | [GameTheory-02-NormalForm.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm.ipynb) | GameTheory-02-NormalForm | Python 3 | READY | BETA | 45min | po-2024 | -| 6 | [GameTheory-02b-Lean-Definitions.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-02b-Lean-Definitions.ipynb) | GameTheory 2b - Formalisation Lean : Definitions… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | -| 7 | [GameTheory-02c-Travelers-Dilemma-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-02c-Travelers-Dilemma-Csharp.ipynb) | GameTheory-02c : Traveler's Dilemma en C# — le… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 8 | [GameTheory-02c-Travelers-Dilemma.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-02c-Travelers-Dilemma.ipynb) | GameTheory-02c-Travelers-Dilemma | Python 3 | READY | BETA | 30min | po-2024 | -| 9 | [GameTheory-03-Topology2x2-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03-Topology2x2-Csharp.ipynb) | GameTheory-3 : Topologie des Jeux 2×2 — Twin C#… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 10 | [GameTheory-03-Topology2x2.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03-Topology2x2.ipynb) | GameTheory-03-Topology2x2 | Python 3 | READY | BETA | 45min | po-2024 | -| 11 | [GameTheory-03a-Chemins-de-Swaps.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03a-Chemins-de-Swaps.ipynb) | GameTheory-3a — Chemins de swaps : à quelle… | Python 3 | READY | BETA | 30min | po-2024 | -| 12 | [GameTheory-03b-Chambres-et-Murs.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03b-Chambres-et-Murs.ipynb) | GameTheory 3b : Chambres, murs, codimension — les… | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | -| 13 | [GameTheory-03c-Le-Joueur-LLM.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03c-Le-Joueur-LLM.ipynb) | GameTheory-3c — Le joueur LLM dans le tableau… | Python 3 | DEMO | BETA | 30min | po-2024 | -| 14 | [GameTheory-03d-Plan-de-deformation.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03d-Plan-de-deformation.ipynb) | GameTheory-03d — Biens publics non-lineaires :… | Python 3 | READY | BETA | 15min | po-2024 | -| 15 | [GameTheory-03e-Meta-Actions-Tarifees.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03e-Meta-Actions-Tarifees.ipynb) | GameTheory 3e : Meta-Actions Tarifees et Parcours… | Python 3 | READY | BETA | 45min | po-2024 | -| 16 | [GameTheory-03h-Deux-Especes-de-Fleches.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03h-Deux-Especes-de-Fleches.ipynb) | GameTheory-03h — Deux espèces de flèches : quand… | Python 3 | READY | BETA | 30min | po-2024 | -| 17 | [GameTheory-04-NashEquilibrium-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04-NashEquilibrium-Csharp.ipynb) | GameTheory-04-NashEquilibrium (C#) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 18 | [GameTheory-04-NashEquilibrium.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04-NashEquilibrium.ipynb) | GameTheory-04-NashEquilibrium | Python 3 | READY | BETA | 30min | po-2024 | -| 19 | [GameTheory-04b-Lean-NashExistence.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04b-Lean-NashExistence.ipynb) | GameTheory 4b - Theoreme d'Existence de Nash… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | -| 20 | [GameTheory-04c-NashExistence-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04c-NashExistence-Csharp.ipynb) | GameTheory 4c - Théorème d'Existence de Nash (C#) | .NET (C#) | READY | ALPHA | 45min | po-2024 | +| 5 | [GameTheory-02-NormalForm-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm-Python.ipynb) | GameTheory-02-NormalForm-Python | Python 3 | READY | BETA | 45min | po-2024 | +| 6 | [GameTheory-02b-Lean-Definitions-Lean.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-02b-Lean-Definitions-Lean.ipynb) | GameTheory 2b - Formalisation Lean : Definitions… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 7 | [GameTheory-02c-Travelers-Dilemma-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-02c-Travelers-Dilemma-CSharp.ipynb) | GameTheory-02c : Traveler's Dilemma en C# — le… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 8 | [GameTheory-02c-Travelers-Dilemma-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-02c-Travelers-Dilemma-Python.ipynb) | GameTheory-02c-Travelers-Dilemma-Python | Python 3 | READY | BETA | 30min | po-2024 | +| 9 | [GameTheory-03-Topology2x2-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03-Topology2x2-CSharp.ipynb) | GameTheory-3 : Topologie des Jeux 2×2 — Twin C#… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 10 | [GameTheory-03-Topology2x2-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03-Topology2x2-Python.ipynb) | GameTheory-03-Topology2x2-Python | Python 3 | READY | BETA | 45min | po-2024 | +| 11 | [GameTheory-03b-Chemins-de-Swaps-Lean-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03b-Chemins-de-Swaps-Lean-Python.ipynb) | GameTheory-3a — Chemins de swaps : à quelle… | Python 3 | READY | BETA | 30min | po-2024 | +| 12 | [GameTheory-03c-Chambres-et-Murs-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03c-Chambres-et-Murs-Python.ipynb) | GameTheory 3b : Chambres, murs, codimension — les… | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | +| 13 | [GameTheory-03d-Le-Joueur-LLM-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03d-Le-Joueur-LLM-Python.ipynb) | GameTheory-3c — Le joueur LLM dans le tableau… | Python 3 | DEMO | BETA | 30min | po-2024 | +| 14 | [GameTheory-03e-Plan-de-deformation-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03e-Plan-de-deformation-Python.ipynb) | GameTheory-03d — Biens publics non-lineaires :… | Python 3 | READY | BETA | 30min | po-2024 | +| 15 | [GameTheory-03f-Meta-Actions-Tarifees-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03f-Meta-Actions-Tarifees-Python.ipynb) | GameTheory 3e : Meta-Actions Tarifees et Parcours… | Python 3 | READY | BETA | 45min | po-2024 | +| 16 | [GameTheory-03g-Deux-Especes-de-Fleches-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-03g-Deux-Especes-de-Fleches-Python.ipynb) | GameTheory-03h — Deux espèces de flèches : quand… | Python 3 | READY | BETA | 30min | po-2024 | +| 17 | [GameTheory-04-NashEquilibrium-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04-NashEquilibrium-CSharp.ipynb) | GameTheory-04-NashEquilibrium-Python (C#) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 18 | [GameTheory-04-NashEquilibrium-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04-NashEquilibrium-Python.ipynb) | GameTheory-04-NashEquilibrium-Python | Python 3 | READY | BETA | 30min | po-2024 | +| 19 | [GameTheory-04b-Lean-NashExistence-Lean.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04b-Lean-NashExistence-Lean.ipynb) | GameTheory 4b - Theoreme d'Existence de Nash… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 20 | [GameTheory-04c-NashExistence-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04c-NashExistence-CSharp.ipynb) | GameTheory 4c - Théorème d'Existence de Nash (C#) | .NET (C#) | READY | ALPHA | 45min | po-2024 | | 21 | [GameTheory-04c-NashExistence-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04c-NashExistence-Python.ipynb) | GameTheory 4c - Theoreme d'Existence de Nash… | Python 3 | READY | BETA | 45min | po-2024 | -| 22 | [GameTheory-04d-Marchandage-Asymetrique.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04d-Marchandage-Asymetrique.ipynb) | GameTheory-04d-Marchandage-Asymetrique | Python 3 | READY | BETA | 30min | po-2024 | -| 23 | [GameTheory-04e-Reflective-Oracles.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04e-Reflective-Oracles.ipynb) | GameTheory 04e — Oracles réflexifs, décision… | Python 3 | READY | BETA | 45min | po-2024 | -| 24 | [GameTheory-04f-Theories-Decision-Predicteur.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04f-Theories-Decision-Predicteur.ipynb) | GameTheory 04f — Théories de la décision face à un… | Python 3 | READY | BETA | 45min | po-2024 | -| 25 | [GameTheory-05-ZeroSum-Minimax-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-05-ZeroSum-Minimax-Csharp.ipynb) | GameTheory-05-ZeroSum-Minimax (Twin C#) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 26 | [GameTheory-05-ZeroSum-Minimax.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-05-ZeroSum-Minimax.ipynb) | GameTheory-05-ZeroSum-Minimax | Python 3 | READY | BETA | 30min | po-2024 | -| 27 | [GameTheory-05b-Lean-Minimax.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-05b-Lean-Minimax.ipynb) | GameTheory-5b — Théorème minimax de von Neumann… | Lean 4 (WSL) | READY | BETA | 15min | po-2024 | -| 28 | [GameTheory-06-EvolutionTrust-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06-EvolutionTrust-Csharp.ipynb) | GameTheory-6 : Évolution et Confiance — Twin C#… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 29 | [GameTheory-06-EvolutionTrust.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06-EvolutionTrust.ipynb) | GameTheory-06-EvolutionTrust | Python 3 | READY | BETA | 45min | po-2024 | -| 30 | [GameTheory-06b-Lean-RepeatedGames.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06b-Lean-RepeatedGames.ipynb) | GameTheory-6b — Jeux répétés en Lean : le lake… | Python 3 | READY | DRAFT | 30min | po-2024 | -| 31 | [GameTheory-06c-RepeatedGames-FolkTheorem-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06c-RepeatedGames-FolkTheorem-Csharp.ipynb) | GameTheory-6c (C#) : Jeux Répétés et Théorème Folk | .NET (C#) | READY | BETA | 45min | po-2024 | -| 32 | [GameTheory-06c-RepeatedGames-FolkTheorem.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06c-RepeatedGames-FolkTheorem.ipynb) | GameTheory-6c : Jeux Répétés et Théorème Folk… | Python 3 | READY | BETA | 30min | po-2024 | -| 33 | [GameTheory-06d-Sympathie-vs-Engagement.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06d-Sympathie-vs-Engagement.ipynb) | GameTheory-06d : Sympathie contre Engagement — la… | Python 3 | READY | BETA | 30min | po-2024 | -| 34 | [GameTheory-06e-Open-Source-Game-Theory.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06e-Open-Source-Game-Theory.ipynb) | GameTheory-06e : Transparence des programmes et… | Python 3 (ipykernel) | READY | ALPHA | 15min | po-2024 | -| 35 | [GameTheory-06f-Bounded-Agents-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06f-Bounded-Agents-Python.ipynb) | Agents-programmes a budget explicite - compagnon… | Python 3 | READY | DRAFT | 30min | po-2024 | -| 36 | [GameTheory-06f-Bounded-Proofs-Reasoning-Costs.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06f-Bounded-Proofs-Reasoning-Costs.ipynb) | GameTheory-06f — Preuves bornees et cout du… | Python 3 | READY | BETA | 30min | po-2024 | -| 37 | [GameTheory-06g-Bounded-Agents-Lean.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06g-Bounded-Agents-Lean.ipynb) | GameTheory-06g — Agents à budget explicite… | Lean (WSL) | BROKEN | DRAFT | 30min | po-2024 | -| 38 | [GameTheory-06g-Simulation-Based-Program-Equilibria.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06g-Simulation-Based-Program-Equilibria.ipynb) | GameTheory-06g — Équilibres de jeux-programmes… | Python 3 | READY | BETA | 30min | po-2024 | -| 39 | [GameTheory-06h-Transparent-Institutions.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06h-Transparent-Institutions.ipynb) | GameTheory-06h — Programmes transparents comme… | Python 3 | READY | BETA | 45min | po-2024 | -| 40 | [GameTheory-07-ExtensiveForm-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-07-ExtensiveForm-Csharp.ipynb) | GameTheory-07-ExtensiveForm (Twin C#) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 41 | [GameTheory-07-ExtensiveForm.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-07-ExtensiveForm.ipynb) | GameTheory-07-ExtensiveForm | Python 3 | READY | BETA | 45min | po-2024 | -| 42 | [GameTheory-08-CombinatorialGames-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-08-CombinatorialGames-Csharp.ipynb) | GameTheory-08-CombinatorialGames (C#) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 43 | [GameTheory-08-CombinatorialGames.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-08-CombinatorialGames.ipynb) | GameTheory 8 - Jeux Combinatoires | Python 3 | READY | BETA | 30min | po-2024 | -| 44 | [GameTheory-08b-Lean-CombinatorialGames.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-08b-Lean-CombinatorialGames.ipynb) | GameTheory 8b - Jeux Combinatoires en Lean | Lean 4 (WSL) | READY | BETA | 15min | po-2024 | -| 45 | [GameTheory-08c-CombinatorialGames-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-08c-CombinatorialGames-Csharp.ipynb) | GameTheory 8c - Jeux Combinatoires :… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 46 | [GameTheory-08c-CombinatorialGames-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-08c-CombinatorialGames-Python.ipynb) | GameTheory 8c - Jeux Combinatoires :… | Python 3 | READY | BETA | 30min | po-2024 | -| 47 | [GameTheory-08d-Lean-CGT-Native.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-08d-Lean-CGT-Native.ipynb) | GameTheory 8d - Combinatorial Games natif : le… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 48 | [GameTheory-09-BackwardInduction-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-09-BackwardInduction-Csharp.ipynb) | GameTheory-09-BackwardInduction (C#) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 49 | [GameTheory-09-BackwardInduction.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-09-BackwardInduction.ipynb) | GameTheory-09-BackwardInduction | Python 3 | READY | BETA | 45min | po-2024 | -| 50 | [GameTheory-09b-Commitment-Stackelberg.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-09b-Commitment-Stackelberg.ipynb) | Stackelberg : la performativité sans mystère | Python 3 | READY | BETA | 30min | po-2024 | -| 51 | [GameTheory-09c-Stackelberg-SecurityGame.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-09c-Stackelberg-SecurityGame.ipynb) | GameTheory-09c : Stackelberg Security Game —… | Python 3 | READY | BETA | 15min | po-2024 | -| 52 | [GameTheory-10-ForwardInduction-SPE-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-10-ForwardInduction-SPE-Csharp.ipynb) | GameTheory-10 — Équilibres Parfaits de Sous-Jeux… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 53 | [GameTheory-10-ForwardInduction-SPE.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-10-ForwardInduction-SPE.ipynb) | GameTheory-10-ForwardInduction-SPE | Python 3 | READY | BETA | 45min | po-2024 | -| 54 | [GameTheory-11-BayesianGames-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-11-BayesianGames-Csharp.ipynb) | GameTheory-11-BayesianGames-Csharp | .NET (C#) | READY | BETA | 45min | po-2024 | -| 55 | [GameTheory-11-BayesianGames.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-11-BayesianGames.ipynb) | GameTheory-11-BayesianGames | Python 3 | READY | BETA | 45min | po-2024 | -| 56 | [GameTheory-11b-Lean-BayesianGamesExt.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-11b-Lean-BayesianGamesExt.ipynb) | GameTheory-11b — Jeux Bayésiens en Lean 4… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | -| 57 | [GameTheory-12-ReputationGames-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-12-ReputationGames-Csharp.ipynb) | GameTheory-12 — Jeux de Réputation (twin C# du… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 58 | [GameTheory-12-ReputationGames.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-12-ReputationGames.ipynb) | GameTheory-12-ReputationGames | Python 3 | READY | BETA | 30min | po-2024 | -| 59 | [GameTheory-13-ImperfectInfo-CFR-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-13-ImperfectInfo-CFR-Csharp.ipynb) | GameTheory-13 : Jeux a Information Imparfaite et… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 60 | [GameTheory-13-ImperfectInfo-CFR.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-13-ImperfectInfo-CFR.ipynb) | GameTheory-13 : Jeux a Information Imparfaite et… | Python (GameTheory WSL +… | READY | BETA | 1h | po-2024 | -| 61 | [GameTheory-13b-Safe-Subgame-Solving.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-13b-Safe-Subgame-Solving.ipynb) | GameTheory-13b : Safe Subgame Solving -- quand le… | Python (coursia-ml-training) | READY | BETA | 30min | po-2024 | -| 62 | [GameTheory-13c-Safe-Subgame-Solving-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-13c-Safe-Subgame-Solving-Csharp.ipynb) | GameTheory-13c : Safe Subgame Solving en C# — le… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 63 | [GameTheory-13d-Optimistic-CFR.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-13d-Optimistic-CFR.ipynb) | GameTheory-13d : Optimistic Counterfactual Regret… | Python 3 | READY | BETA | 15min | po-2024 | -| 64 | [GameTheory-14-DifferentialGames-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames-Csharp.ipynb) | GameTheory-14 : Jeux Differentiels et Equilibres… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 65 | [GameTheory-14-DifferentialGames.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames.ipynb) | GameTheory-14 : Jeux Differentiels et Equilibres… | Python 3 | READY | BETA | 45min | po-2024 | -| 66 | [GameTheory-15-CooperativeGames-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames-Csharp.ipynb) | GameTheory-15 — Jeux Coopératifs (Twin C#) | .NET (C#) | READY | BETA | 1h | po-2024 | -| 67 | [GameTheory-15-CooperativeGames.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames.ipynb) | GameTheory-15-CooperativeGames | Python 3 (ipykernel) | READY | BETA | 1h | po-2024 | -| 68 | [GameTheory-15b-Lean-CooperativeGames.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15b-Lean-CooperativeGames.ipynb) | GameTheory 15b - Jeux Cooperatifs en Lean :… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | -| 69 | [GameTheory-15c-CooperativeGames-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-Csharp.ipynb) | GameTheory 15c - Jeux Cooperatifs (C# / .NET) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 70 | [GameTheory-15c-CooperativeGames-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-Python.ipynb) | GameTheory 15c - Jeux Cooperatifs Lean (Python) | Python (coursia-ml-training) | READY | BETA | 45min | po-2024 | -| 71 | [GameTheory-15d-Mobius-Coalitions.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15d-Mobius-Coalitions.ipynb) | GameTheory 15d - La decomposition de Mobius sur le… | Python 3 | READY | BETA | 30min | po-2024 | -| 72 | [GameTheory-15e-Coalition-Power-SMT.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15e-Coalition-Power-SMT.ipynb) | GameTheory-15e — Pouvoir coalitionnel : calcul,… | Python 3 | READY | BETA | 30min | po-2024 | -| 73 | [GameTheory-15f-Shapley-Groupes.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15f-Shapley-Groupes.ipynb) | GameTheory 15f - Valeur de Shapley de groupe :… | Python 3 | READY | BETA | 45min | po-2024 | -| 74 | [GameTheory-15g-AssistanceGames-2026-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15g-AssistanceGames-2026-Python.ipynb) | GameTheory 15g - Assistance Games (résultat 2026) | Python 3 (c820) | READY | BETA | 30min | po-2024 | -| 75 | [GameTheory-16-MechanismDesign-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign-Csharp.ipynb) | GameTheory-16-MechanismDesign (C#) | .NET (C#) | READY | BETA | 30min | po-2024 | -| 76 | [GameTheory-16-MechanismDesign.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign.ipynb) | GameTheory-16 : Théorie des Mécanismes et Principe… | Python 3 | READY | BETA | 45min | po-2024 | -| 77 | [GameTheory-16b-Automated-Mechanism-Design.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16b-Automated-Mechanism-Design.ipynb) | GameTheory-16b : Automated Mechanism Design (AMD) | Python 3 | READY | BETA | 15min | po-2024 | -| 78 | [GameTheory-16c-Extraction-de-Revenu-DSIC-IR.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16c-Extraction-de-Revenu-DSIC-IR.ipynb) | GameTheory-16c : La dimension paiement que le… | Python 3 | READY | BETA | 15min | po-2024 | -| 79 | [GameTheory-16d-Echange-de-Reins.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16d-Echange-de-Reins.ipynb) | GameTheory-16d — L'echange de reins : de la valeur… | Python 3 | READY | BETA | 30min | po-2024 | -| 80 | [GameTheory-16e-LLM-Players-Othman-Sandholm.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16e-LLM-Players-Othman-Sandholm.ipynb) | GameTheory-16e : Pilote — joueurs LLM hétérogènes… | Python 3 | READY | BETA | 45min | po-2024 | -| 81 | [GameTheory-17-MultiAgent-RL-Csharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL-Csharp.ipynb) | GameTheory-17 (C#) : Multi-Agent Reinforcement… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 82 | [GameTheory-17-MultiAgent-RL.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL.ipynb) | GameTheory-17 : Apprentissage par Renforcement… | Python (GameTheory WSL +… | READY | BETA | 30min | po-2024 | -| 83 | [GameTheory-17b-Asymmetric-Information.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-17b-Asymmetric-Information.ipynb) | Information asymétrique : types privés,… | Python 3 | READY | BETA | 30min | po-2024 | -| 84 | [GameTheory-17c-Lean-Lemons-Certificat.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-17c-Lean-Lemons-Certificat.ipynb) | Le marché des lemons : le certificat formel… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 85 | [GameTheory-17c-Market-to-Balance-Sheet.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-17c-Market-to-Balance-Sheet.ipynb) | Du marché au bilan : le pont théorie des jeux… | Python 3 | READY | BETA | 30min | po-2024 | -| 86 | [GameTheory-17d-Lean-Screening-Signaling.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-17d-Lean-Screening-Signaling.ipynb) | Screening, signal et anticipation : les trois… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 87 | [GameTheory-18-Open-Games-et-Lentilles.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-18-Open-Games-et-Lentilles.ipynb) | GameTheory-18 : Open Games et Lentilles -- la… | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | -| 88 | [GameTheory-18b-Casser-la-Composition.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-18b-Casser-la-Composition.ipynb) | GameTheory-18b : Casser la composition — où la… | Python 3 | READY | BETA | 30min | po-2024 | -| 89 | [GameTheory-19-Abstraction-a-Dette.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-19-Abstraction-a-Dette.ipynb) | GameTheory-19 : L'abstraction a dette mesurable | Python 3 | READY | BETA | 15min | po-2024 | -| 90 | [GameTheory-20-Chemin-Minimal-Robinson-Goforth.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-20-Chemin-Minimal-Robinson-Goforth.ipynb) | GameTheory 24 : Le chemin minimal, témoin… | Python 3 | READY | DRAFT | 45min | po-2024 | -| 91 | [GameTheory-20b-Chemin-Minimal-Temoins-Impossibilite.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-20b-Chemin-Minimal-Temoins-Impossibilite.ipynb) | GameTheory 24b : Le temoin d'impossibilite | Python 3 | READY | BETA | 30min | po-2024 | -| 92 | [GameTheory-20c-Chemin-Minimal-3x2-Ordinal.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-20c-Chemin-Minimal-3x2-Ordinal.ipynb) | GameTheory 20c : Le chemin minimal sur un second… | Python 3 | READY | BETA | 45min | po-2024 | -| 93 | [GameTheory-21-Loi-II-Translateur-Life.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-21-Loi-II-Translateur-Life.ipynb) | GameTheory-21 — Loi II, seconde jambe :… | Python 3 | READY | BETA | 30min | po-2024 | -| 94 | [GameTheory-22-Ensembles-Limites-Poincare-Bendixson.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-22-Ensembles-Limites-Poincare-Bendixson.ipynb) | GameTheory-22 — Ensembles limites :… | Python 3 | READY | BETA | 30min | po-2024 | -| 95 | [GameTheory-23-Munkres-Assignment.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-23-Munkres-Assignment.ipynb) | GameTheory-23 — L'algorithme de Kuhn-Munkres :… | Python 3 | READY | BETA | 30min | po-2024 | -| 96 | [GameTheory-23b-Lean-Assignment-Native.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-23b-Lean-Assignment-Native.ipynb) | GameTheory 23b — Le lake assignment_lean par son… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 97 | [GameTheory-24-Humour-Banc.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-24-Humour-Banc.ipynb) | GameTheory-24 : Banc de calibration — humour,… | Python (CoursIA-2 venv) | READY | BETA | 30min | po-2024 | -| 98 | [GameTheory-24b-Humour-Banc-Dur.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-24b-Humour-Banc-Dur.ipynb) | GameTheory-24b : Banc humour — passer à l'échelle | Python 3 | READY | BETA | 45min | po-2024 | -| 99 | [GameTheory-25-Bayesian-Persuasion.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-25-Bayesian-Persuasion.ipynb) | GameTheory-25 — Persuasion bayésienne :… | Python 3 | READY | DRAFT | 30min | po-2024 | +| 22 | [GameTheory-04d-Marchandage-Asymetrique-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04d-Marchandage-Asymetrique-Python.ipynb) | GameTheory-04d-Marchandage-Asymetrique-Python | Python 3 | READY | ALPHA | 30min | po-2024 | +| 23 | [GameTheory-04e-Reflective-Oracles-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04e-Reflective-Oracles-Python.ipynb) | GameTheory 04e — Oracles réflexifs, décision… | Python 3 | READY | BETA | 45min | po-2024 | +| 24 | [GameTheory-04f-Theories-Decision-Predicteur-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-04f-Theories-Decision-Predicteur-Python.ipynb) | GameTheory 04f — Théories de la décision face à un… | Python 3 | READY | BETA | 45min | po-2024 | +| 25 | [GameTheory-05-ZeroSum-Minimax-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-05-ZeroSum-Minimax-CSharp.ipynb) | GameTheory-05-ZeroSum-Minimax-Python (Twin C#) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 26 | [GameTheory-05-ZeroSum-Minimax-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-05-ZeroSum-Minimax-Python.ipynb) | GameTheory-05-ZeroSum-Minimax-Python | Python 3 | READY | BETA | 30min | po-2024 | +| 27 | [GameTheory-05b-Lean-Minimax-Lean.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-05b-Lean-Minimax-Lean.ipynb) | GameTheory-5b — Théorème minimax de von Neumann… | Lean 4 (WSL) | READY | BETA | 15min | po-2024 | +| 28 | [GameTheory-06-EvolutionTrust-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06-EvolutionTrust-CSharp.ipynb) | GameTheory-6 : Évolution et Confiance — Twin C#… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 29 | [GameTheory-06-EvolutionTrust-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06-EvolutionTrust-Python.ipynb) | GameTheory-06-EvolutionTrust-Python | Python 3 | READY | BETA | 45min | po-2024 | +| 30 | [GameTheory-06b-Lean-RepeatedGames-Lean-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06b-Lean-RepeatedGames-Lean-Python.ipynb) | GameTheory-6b — Jeux répétés en Lean : le lake… | Python 3 | READY | DRAFT | 30min | po-2024 | +| 31 | [GameTheory-06c-RepeatedGames-FolkTheorem-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06c-RepeatedGames-FolkTheorem-CSharp.ipynb) | GameTheory-6c (C#) : Jeux Répétés et Théorème Folk | .NET (C#) | READY | BETA | 45min | po-2024 | +| 32 | [GameTheory-06c-RepeatedGames-FolkTheorem-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06c-RepeatedGames-FolkTheorem-Python.ipynb) | GameTheory-6c : Jeux Répétés et Théorème Folk… | Python 3 | READY | BETA | 30min | po-2024 | +| 33 | [GameTheory-06d-Sympathie-vs-Engagement-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06d-Sympathie-vs-Engagement-Python.ipynb) | GameTheory-06d : Sympathie contre Engagement — la… | Python 3 | READY | BETA | 30min | po-2024 | +| 34 | [GameTheory-06e-Open-Source-Game-Theory-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06e-Open-Source-Game-Theory-Python.ipynb) | GameTheory-06e : Transparence des programmes et… | Python 3 (ipykernel) | READY | ALPHA | 15min | po-2024 | +| 35 | [GameTheory-06f-Bounded-Agents-Lean.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06f-Bounded-Agents-Lean.ipynb) | GameTheory-06g — Agents à budget explicite… | Lean (WSL) | READY | BETA | 30min | po-2024 | +| 36 | [GameTheory-06f-Bounded-Agents-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06f-Bounded-Agents-Python.ipynb) | Agents-programmes a budget explicite - compagnon… | Python 3 | READY | DRAFT | 30min | po-2024 | +| 37 | [GameTheory-06g-Simulation-Based-Program-Equilibria-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06g-Simulation-Based-Program-Equilibria-Python.ipynb) | GameTheory-06g — Équilibres de jeux-programmes… | Python 3 | READY | BETA | 30min | po-2024 | +| 38 | [GameTheory-06h-Transparent-Institutions-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06h-Transparent-Institutions-Python.ipynb) | GameTheory-06h — Programmes transparents comme… | Python 3 | READY | BETA | 45min | po-2024 | +| 39 | [GameTheory-06i-Ensembles-Limites-Poincare-Bendixson-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06i-Ensembles-Limites-Poincare-Bendixson-Python.ipynb) | GameTheory-06i — Ensembles limites :… | Python 3 | READY | BETA | 30min | po-2024 | +| 40 | [GameTheory-06j-Bounded-Proofs-Reasoning-Costs-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-06j-Bounded-Proofs-Reasoning-Costs-Python.ipynb) | GameTheory-06f — Preuves bornees et cout du… | Python 3 | READY | BETA | 30min | po-2024 | +| 41 | [GameTheory-07-ExtensiveForm-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-07-ExtensiveForm-CSharp.ipynb) | GameTheory-07-ExtensiveForm-Python (Twin C#) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 42 | [GameTheory-07-ExtensiveForm-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-07-ExtensiveForm-Python.ipynb) | GameTheory-07-ExtensiveForm-Python | Python 3 | READY | BETA | 45min | po-2024 | +| 43 | [GameTheory-08-CombinatorialGames-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-08-CombinatorialGames-CSharp.ipynb) | GameTheory 8 - Jeux Combinatoires (Twin C#) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 44 | [GameTheory-08-CombinatorialGames-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-08-CombinatorialGames-Python.ipynb) | GameTheory 8 - Jeux Combinatoires | Python 3 | READY | BETA | 30min | po-2024 | +| 45 | [GameTheory-08b-Lean-CombinatorialGames-Lean.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-08b-Lean-CombinatorialGames-Lean.ipynb) | GameTheory 8b - Jeux Combinatoires en Lean | Lean 4 (WSL) | READY | BETA | 15min | po-2024 | +| 46 | [GameTheory-08c-CombinatorialGames-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-08c-CombinatorialGames-CSharp.ipynb) | GameTheory 8c - Jeux Combinatoires :… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 47 | [GameTheory-08c-CombinatorialGames-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-08c-CombinatorialGames-Python.ipynb) | GameTheory 8c - Jeux Combinatoires :… | Python 3 | READY | BETA | 30min | po-2024 | +| 48 | [GameTheory-08d-Lean-CGT-Lean.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-08d-Lean-CGT-Lean.ipynb) | GameTheory 8d - Combinatorial Games natif : le… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 49 | [GameTheory-09-BackwardInduction-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-09-BackwardInduction-CSharp.ipynb) | GameTheory-09-BackwardInduction-Python (C#) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 50 | [GameTheory-09-BackwardInduction-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-09-BackwardInduction-Python.ipynb) | GameTheory-09-BackwardInduction-Python | Python 3 | READY | BETA | 45min | po-2024 | +| 51 | [GameTheory-09b-Commitment-Stackelberg-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-09b-Commitment-Stackelberg-Python.ipynb) | Stackelberg : la performativité sans mystère | Python 3 | READY | BETA | 30min | po-2024 | +| 52 | [GameTheory-09c-Stackelberg-SecurityGame-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-09c-Stackelberg-SecurityGame-Python.ipynb) | GameTheory-09c : Stackelberg Security Game —… | Python 3 | READY | BETA | 15min | po-2024 | +| 53 | [GameTheory-10-ForwardInduction-SPE-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-10-ForwardInduction-SPE-CSharp.ipynb) | GameTheory-10 — Équilibres Parfaits de Sous-Jeux… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 54 | [GameTheory-10-ForwardInduction-SPE-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-10-ForwardInduction-SPE-Python.ipynb) | GameTheory-10-ForwardInduction-SPE-Python | Python 3 | READY | BETA | 45min | po-2024 | +| 55 | [GameTheory-11-BayesianGames-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-11-BayesianGames-CSharp.ipynb) | GameTheory-11-BayesianGames-CSharp | .NET (C#) | READY | BETA | 45min | po-2024 | +| 56 | [GameTheory-11-BayesianGames-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-11-BayesianGames-Python.ipynb) | GameTheory-11-BayesianGames-Python | Python 3 | READY | BETA | 45min | po-2024 | +| 57 | [GameTheory-11b-Lean-BayesianGamesExt-Lean.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-11b-Lean-BayesianGamesExt-Lean.ipynb) | GameTheory-11b — Jeux Bayésiens en Lean 4… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 58 | [GameTheory-12-ReputationGames-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-12-ReputationGames-CSharp.ipynb) | GameTheory-12 — Jeux de Réputation (twin C# du… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 59 | [GameTheory-12-ReputationGames-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-12-ReputationGames-Python.ipynb) | GameTheory-12-ReputationGames-Python | Python 3 | READY | BETA | 30min | po-2024 | +| 60 | [GameTheory-13-ImperfectInfo-CFR-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-13-ImperfectInfo-CFR-CSharp.ipynb) | GameTheory-13 : Jeux a Information Imparfaite et… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 61 | [GameTheory-13-ImperfectInfo-CFR-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-13-ImperfectInfo-CFR-Python.ipynb) | GameTheory-13 : Jeux a Information Imparfaite et… | Python (GameTheory WSL +… | READY | BETA | 1h | po-2024 | +| 62 | [GameTheory-13b-Safe-Subgame-Solving-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-13b-Safe-Subgame-Solving-Python.ipynb) | GameTheory-13b : Safe Subgame Solving -- quand le… | Python (coursia-ml-training) | READY | BETA | 30min | po-2024 | +| 63 | [GameTheory-13c-Safe-Subgame-Solving-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-13c-Safe-Subgame-Solving-CSharp.ipynb) | GameTheory-13c : Safe Subgame Solving en C# — le… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 64 | [GameTheory-13d-Optimistic-CFR-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-13d-Optimistic-CFR-Python.ipynb) | GameTheory-13d : Optimistic Counterfactual Regret… | Python 3 | READY | BETA | 15min | po-2024 | +| 65 | [GameTheory-14-DifferentialGames-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames-CSharp.ipynb) | GameTheory-14 : Jeux Differentiels et Equilibres… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 66 | [GameTheory-14-DifferentialGames-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames-Python.ipynb) | GameTheory-14 : Jeux Differentiels et Equilibres… | Python 3 | READY | BETA | 45min | po-2024 | +| 67 | [GameTheory-15-CooperativeGames-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames-CSharp.ipynb) | GameTheory-15 — Jeux Coopératifs (Twin C#) | .NET (C#) | READY | BETA | 1h | po-2024 | +| 68 | [GameTheory-15-CooperativeGames-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames-Python.ipynb) | GameTheory-15-CooperativeGames-Python | Python 3 (ipykernel) | READY | BETA | 1h | po-2024 | +| 69 | [GameTheory-15b-Lean-CooperativeGames-Lean.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15b-Lean-CooperativeGames-Lean.ipynb) | GameTheory 15b - Jeux Cooperatifs en Lean :… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 70 | [GameTheory-15c-CooperativeGames-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-CSharp.ipynb) | GameTheory 15c - Jeux Cooperatifs (C# / .NET) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 71 | [GameTheory-15c-CooperativeGames-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-Python.ipynb) | GameTheory 15c - Jeux Cooperatifs Lean (Python) | Python (coursia-ml-training) | READY | BETA | 45min | po-2024 | +| 72 | [GameTheory-15d-Mobius-Coalitions-Lean-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15d-Mobius-Coalitions-Lean-Python.ipynb) | GameTheory 15d - La decomposition de Mobius sur le… | Python 3 | READY | BETA | 30min | po-2024 | +| 73 | [GameTheory-15e-Coalition-Power-SMT-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15e-Coalition-Power-SMT-Python.ipynb) | GameTheory-15e — Pouvoir coalitionnel : calcul,… | Python 3 | READY | BETA | 30min | po-2024 | +| 74 | [GameTheory-15f-Shapley-Groupes-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15f-Shapley-Groupes-Python.ipynb) | GameTheory 15f - Valeur de Shapley de groupe :… | Python 3 | READY | BETA | 45min | po-2024 | +| 75 | [GameTheory-15g-AssistanceGames-2026-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-15g-AssistanceGames-2026-Python.ipynb) | GameTheory 15g - Assistance Games (résultat 2026) | Python 3 (c820) | READY | BETA | 30min | po-2024 | +| 76 | [GameTheory-16-MechanismDesign-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign-CSharp.ipynb) | GameTheory-16-MechanismDesign-Python (C#) | .NET (C#) | READY | BETA | 30min | po-2024 | +| 77 | [GameTheory-16-MechanismDesign-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign-Python.ipynb) | GameTheory-16 : Théorie des Mécanismes et Principe… | Python 3 | READY | BETA | 45min | po-2024 | +| 78 | [GameTheory-16b-Automated-Mechanism-Design-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16b-Automated-Mechanism-Design-Python.ipynb) | GameTheory-16b : Automated Mechanism Design (AMD) | Python 3 | READY | BETA | 15min | po-2024 | +| 79 | [GameTheory-16c-Extraction-de-Revenu-DSIC-IR-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16c-Extraction-de-Revenu-DSIC-IR-Python.ipynb) | GameTheory-16c : La dimension paiement que le… | Python 3 | READY | BETA | 15min | po-2024 | +| 80 | [GameTheory-16d-Echange-de-Reins-Lean-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16d-Echange-de-Reins-Lean-Python.ipynb) | GameTheory-16d — L'echange de reins : de la valeur… | Python 3 | READY | BETA | 30min | po-2024 | +| 81 | [GameTheory-16e-LLM-Players-Othman-Sandholm-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16e-LLM-Players-Othman-Sandholm-Python.ipynb) | GameTheory-16e : Pilote — joueurs LLM hétérogènes… | Python 3 | READY | BETA | 45min | po-2024 | +| 82 | [GameTheory-16f-Lean-Assignment-Lean.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16f-Lean-Assignment-Lean.ipynb) | GameTheory 23b — Le lake assignment_lean par son… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 83 | [GameTheory-16f-Munkres-Assignment-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16f-Munkres-Assignment-Python.ipynb) | GameTheory-23 — L'algorithme de Kuhn-Munkres :… | Python 3 | READY | BETA | 30min | po-2024 | +| 84 | [GameTheory-17-MultiAgent-RL-CSharp.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL-CSharp.ipynb) | GameTheory-17 (C#) : Multi-Agent Reinforcement… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 85 | [GameTheory-17-MultiAgent-RL-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL-Python.ipynb) | GameTheory-17 : Apprentissage par Renforcement… | Python (GameTheory WSL +… | READY | BETA | 30min | po-2024 | +| 86 | [GameTheory-17b-Asymmetric-Information-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-17b-Asymmetric-Information-Python.ipynb) | Information asymétrique : types privés,… | Python 3 | READY | BETA | 30min | po-2024 | +| 87 | [GameTheory-17c-Lean-Lemons-Certificat-Lean.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-17c-Lean-Lemons-Certificat-Lean.ipynb) | Le marché des lemons : le certificat formel… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 88 | [GameTheory-17d-Lean-Screening-Signaling-Lean.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-17d-Lean-Screening-Signaling-Lean.ipynb) | Screening, signal et anticipation : les trois… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 89 | [GameTheory-17e-Bayesian-Persuasion-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-17e-Bayesian-Persuasion-Python.ipynb) | GameTheory-25 — Persuasion bayésienne :… | Python 3 | READY | DRAFT | 30min | po-2024 | +| 90 | [GameTheory-17f-Market-to-Balance-Sheet-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-17f-Market-to-Balance-Sheet-Python.ipynb) | Du marché au bilan : le pont théorie des jeux… | Python 3 | READY | BETA | 30min | po-2024 | +| 91 | [GameTheory-18-Open-Games-et-Lentilles-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-18-Open-Games-et-Lentilles-Python.ipynb) | GameTheory-18 : Open Games et Lentilles -- la… | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | +| 92 | [GameTheory-18b-Casser-la-Composition-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-18b-Casser-la-Composition-Python.ipynb) | GameTheory-18b : Casser la composition — où la… | Python 3 | READY | BETA | 30min | po-2024 | +| 93 | [GameTheory-18c-Humour-Banc-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-18c-Humour-Banc-Python.ipynb) | GameTheory-24 : Banc de calibration — humour,… | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | +| 94 | [GameTheory-18d-Humour-Banc-Dur-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-18d-Humour-Banc-Dur-Python.ipynb) | GameTheory-18d : Banc humour — passer à l'échelle | Python 3 | READY | BETA | 45min | po-2024 | +| 95 | [GameTheory-19-Abstraction-a-Dette-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-19-Abstraction-a-Dette-Python.ipynb) | GameTheory-19 : L'abstraction a dette mesurable | Python 3 | READY | BETA | 15min | po-2024 | +| 96 | [GameTheory-20-Chemin-Minimal-Robinson-Goforth-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-20-Chemin-Minimal-Robinson-Goforth-Python.ipynb) | GameTheory 20 : Le chemin minimal, témoin… | Python 3 | READY | DRAFT | 45min | po-2024 | +| 97 | [GameTheory-20b-Chemin-Minimal-Temoins-Impossibilite-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-20b-Chemin-Minimal-Temoins-Impossibilite-Python.ipynb) | GameTheory 24b : Le temoin d'impossibilite | Python 3 | READY | BETA | 30min | po-2024 | +| 98 | [GameTheory-20c-Chemin-Minimal-3x2-Ordinal-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-20c-Chemin-Minimal-3x2-Ordinal-Python.ipynb) | GameTheory 20c : Le chemin minimal sur un second… | Python 3 | READY | BETA | 45min | po-2024 | +| 99 | [GameTheory-20d-Loi-II-Translateur-Life-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-20d-Loi-II-Translateur-Life-Python.ipynb) | GameTheory-21 — Loi II, seconde jambe :… | Python 3 | READY | BETA | 30min | po-2024 | #### SocialChoice (10) @@ -1337,65 +1360,66 @@ Total notebooks: 1312 | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| -| 1 | [Sudoku-00-Environment-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-00-Environment-Csharp.ipynb) | Sudoku-00 : Environnement et Classes de Base (C#) | .NET (C#) | READY | BETA | 30min | po-2023 | -| 2 | [Sudoku-01-Backtracking-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-01-Backtracking-Csharp.ipynb) | Sudoku-01 : Résolution par Backtracking | .NET (C#) | READY | BETA | 30min | po-2023 | +| 1 | [Sudoku-00-Environment-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-00-Environment-CSharp.ipynb) | Sudoku-00 : Environnement et Classes de Base (C#) | .NET (C#) | READY | BETA | 30min | po-2023 | +| 2 | [Sudoku-01-Backtracking-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-01-Backtracking-CSharp.ipynb) | Sudoku-01 : Résolution par Backtracking | .NET (C#) | READY | BETA | 30min | po-2023 | | 3 | [Sudoku-01-Backtracking-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-01-Backtracking-Python.ipynb) | Sudoku-01 : Resolution par Backtracking (Python) | Python 3 | READY | BETA | 30min | po-2023 | -| 4 | [Sudoku-02-DancingLinks-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-02-DancingLinks-Csharp.ipynb) | Résolution de Sudoku avec Algorithm X et Dancing… | .NET (C#) | READY | BETA | 45min | po-2023 | +| 4 | [Sudoku-02-DancingLinks-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-02-DancingLinks-CSharp.ipynb) | Résolution de Sudoku avec Algorithm X et Dancing… | .NET (C#) | READY | BETA | 45min | po-2023 | | 5 | [Sudoku-02-DancingLinks-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-02-DancingLinks-Python.ipynb) | Sudoku-Python-DancingLinks : Dancing Links /… | Python 3 | READY | BETA | 30min | po-2023 | -| 6 | [Sudoku-03-Genetic-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-03-Genetic-Csharp.ipynb) | Sudoku-03 : Résolution par Algorithme Génétique… | .NET (C#) | READY | BETA | 45min | po-2023 | +| 6 | [Sudoku-03-Genetic-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-03-Genetic-CSharp.ipynb) | Sudoku-03 : Résolution par Algorithme Génétique… | .NET (C#) | READY | BETA | 45min | po-2023 | | 7 | [Sudoku-03-Genetic-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-03-Genetic-Python.ipynb) | Sudoku-Python-Genetic : Algorithme Génétique… | Python 3 | READY | BETA | 30min | po-2023 | -| 8 | [Sudoku-04-SimulatedAnnealing-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-04-SimulatedAnnealing-Csharp.ipynb) | Résolution de Sudoku par Recuit Simulé | .NET (C#) | READY | BETA | 1h | po-2023 | +| 8 | [Sudoku-04-SimulatedAnnealing-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-04-SimulatedAnnealing-CSharp.ipynb) | Résolution de Sudoku par Recuit Simulé | .NET (C#) | READY | BETA | 1h | po-2023 | | 9 | [Sudoku-04-SimulatedAnnealing-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-04-SimulatedAnnealing-Python.ipynb) | Sudoku-04 : Recuit Simule (Python) | Python 3 | READY | BETA | 45min | po-2023 | -| 10 | [Sudoku-05-PSO-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-05-PSO-Csharp.ipynb) | Sudoku-05 : Particle Swarm Optimization (PSO) | .NET (C#) | READY | BETA | 1h | po-2023 | +| 10 | [Sudoku-05-PSO-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-05-PSO-CSharp.ipynb) | Sudoku-05 : Particle Swarm Optimization (PSO) | .NET (C#) | READY | BETA | 1h | po-2023 | | 11 | [Sudoku-05-PSO-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-05-PSO-Python.ipynb) | Sudoku-05 : Particle Swarm Optimization (Python) | Python 3 | READY | BETA | 45min | po-2023 | -| 12 | [Sudoku-06-AIMA-CSP-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-06-AIMA-CSP-Csharp.ipynb) | Sudoku-06 : Résolution par CSP Académique (AIMA) | .NET (C#) | READY | BETA | 45min | po-2023 | +| 12 | [Sudoku-06-AIMA-CSP-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-06-AIMA-CSP-CSharp.ipynb) | Sudoku-06 : Résolution par CSP Académique (AIMA) | .NET (C#) | READY | BETA | 45min | po-2023 | | 13 | [Sudoku-06-AIMA-CSP-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-06-AIMA-CSP-Python.ipynb) | Sudoku-06 : Résolution par CSP Académique (Python) | Python 3 | READY | BETA | 45min | po-2023 | -| 14 | [Sudoku-07-Norvig-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-07-Norvig-Csharp.ipynb) | Sudoku-07 : Résolution par Propagation de… | .NET (C#) | READY | BETA | 45min | po-2023 | +| 14 | [Sudoku-07-Norvig-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-07-Norvig-CSharp.ipynb) | Sudoku-07 : Résolution par Propagation de… | .NET (C#) | READY | BETA | 45min | po-2023 | | 15 | [Sudoku-07-Norvig-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-07-Norvig-Python.ipynb) | Sudoku-07 : Résolution par Propagation de… | Python 3 | READY | BETA | 30min | po-2023 | -| 16 | [Sudoku-08-HumanStrategies-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-08-HumanStrategies-Csharp.ipynb) | Résolution de Sudoku par Stratégies Humaines | .NET (C#) | READY | BETA | 45min | po-2023 | +| 16 | [Sudoku-08-HumanStrategies-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-08-HumanStrategies-CSharp.ipynb) | Résolution de Sudoku par Stratégies Humaines | .NET (C#) | READY | BETA | 45min | po-2023 | | 17 | [Sudoku-08-HumanStrategies-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-08-HumanStrategies-Python.ipynb) | Sudoku-08 : Resolution par Stratégies Humaines… | Python 3 | READY | BETA | 45min | po-2023 | -| 18 | [Sudoku-09-GraphColoring-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-09-GraphColoring-Csharp.ipynb) | Notebook 9: Résolution de Sudoku par Coloration de… | .NET (C#) | READY | BETA | 45min | po-2023 | +| 18 | [Sudoku-09-GraphColoring-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-09-GraphColoring-CSharp.ipynb) | Notebook 9: Résolution de Sudoku par Coloration de… | .NET (C#) | READY | BETA | 45min | po-2023 | | 19 | [Sudoku-09-GraphColoring-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-09-GraphColoring-Python.ipynb) | Sudoku-09 : Coloration de Graphe (Python) | Python 3 | READY | BETA | 30min | po-2023 | -| 20 | [Sudoku-10-ORTools-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-10-ORTools-Csharp.ipynb) | Sudoku-10 : Résolution avec OR-Tools (C#) | .NET (C#) | READY | BETA | 45min | po-2023 | +| 20 | [Sudoku-10-ORTools-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-10-ORTools-CSharp.ipynb) | Sudoku-10 : Résolution avec OR-Tools (C#) | .NET (C#) | READY | BETA | 45min | po-2023 | | 21 | [Sudoku-10-ORTools-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-10-ORTools-Python.ipynb) | Sudoku-10-ORTools-Python : OR-Tools CP-SAT… | Python 3 | READY | BETA | 30min | po-2023 | -| 22 | [Sudoku-11-Choco-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-11-Choco-Csharp.ipynb) | Sudoku-11-Choco-Csharp : Solveur Choco via IKVM | .NET (C#) | READY | BETA | 45min | po-2023 | +| 22 | [Sudoku-11-Choco-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-11-Choco-CSharp.ipynb) | Sudoku-11-Choco-CSharp : Solveur Choco via IKVM | .NET (C#) | READY | BETA | 45min | po-2023 | | 23 | [Sudoku-11-Choco-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-11-Choco-Python.ipynb) | Notebook 11: Résolution de Sudoku avec Choco… | Python 3 | READY | BETA | 30min | po-2023 | -| 24 | [Sudoku-12-Z3-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-12-Z3-Csharp.ipynb) | Sudoku-12 : Résolution avec Z3 SMT Solver (C#) | .NET (C#) | READY | BETA | 45min | po-2023 | +| 24 | [Sudoku-12-Z3-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-12-Z3-CSharp.ipynb) | Sudoku-12 : Résolution avec Z3 SMT Solver (C#) | .NET (C#) | READY | BETA | 45min | po-2023 | | 25 | [Sudoku-12-Z3-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-12-Z3-Python.ipynb) | Sudoku-12-Z3-Python : Z3 SMT Solver (Python) | Python 3 | READY | BETA | 30min | po-2023 | -| 26 | [Sudoku-12b-Z3-Linq2Z3-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-12b-Z3-Linq2Z3-Csharp.ipynb) | Sudoku 12b : Linq2Z3 — l'histoire d'un binding, de… | .NET (C#) | READY | BETA | 45min | po-2023 | -| 27 | [Sudoku-13-SymbolicAutomata-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-13-SymbolicAutomata-Csharp.ipynb) | Sudoku-13 : Le Sudoku comme Regex Symbolique -… | .NET (C#) | READY | BETA | 1h | po-2023 | +| 26 | [Sudoku-12b-Z3-Linq2Z3-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-12b-Z3-Linq2Z3-CSharp.ipynb) | Sudoku 12b : Linq2Z3 — l'histoire d'un binding, de… | .NET (C#) | READY | BETA | 45min | po-2023 | +| 27 | [Sudoku-13-SymbolicAutomata-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-13-SymbolicAutomata-CSharp.ipynb) | Sudoku-13 : Le Sudoku comme Regex Symbolique -… | .NET (C#) | READY | BETA | 1h | po-2023 | | 28 | [Sudoku-13-SymbolicAutomata-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-13-SymbolicAutomata-Python.ipynb) | Sudoku-13 : Le Sudoku comme Regex Symbolique —… | Python 3 | READY | BETA | 30min | po-2023 | -| 29 | [Sudoku-14-BDD-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-14-BDD-Csharp.ipynb) | Sudoku-14 : Automates avec BDD/MDD - Approche Pure | .NET (C#) | READY | BETA | 45min | po-2023 | +| 29 | [Sudoku-14-BDD-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-14-BDD-CSharp.ipynb) | Sudoku-14 : Automates avec BDD/MDD - Approche Pure | .NET (C#) | READY | BETA | 45min | po-2023 | | 30 | [Sudoku-14-BDD-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-14-BDD-Python.ipynb) | Sudoku-14 : Automates avec BDD/MDD - Approche Pure… | Python 3 | READY | BETA | 30min | po-2023 | -| 31 | [Sudoku-15-Infer-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-15-Infer-Csharp.ipynb) | Résolution de Sudoku avec Infer.NET | .NET (C#) | READY | BETA | 1h | po-2023 | +| 31 | [Sudoku-15-Infer-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-15-Infer-CSharp.ipynb) | Résolution de Sudoku avec Infer.NET | .NET (C#) | READY | BETA | 1h | po-2023 | | 32 | [Sudoku-15-Infer-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-15-Infer-Python.ipynb) | Sudoku-15-Infer-Python : Resolution Probabiliste… | Python 3 | READY | BETA | 45min | po-2023 | | 33 | [Sudoku-16-NeuralNetwork-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-16-NeuralNetwork-Python.ipynb) | Sudoku-16 : Résolution par Réseaux de Neurones | Python 3 | READY | BETA | 1h | po-2023 | | 34 | [Sudoku-17-LLM-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-17-LLM-Python.ipynb) | Notebook 17: Resolution de Sudoku avec Large… | Python 3 | DEMO | BETA | 45min | po-2023 | -| 35 | [Sudoku-18-Comparison-Csharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-18-Comparison-Csharp.ipynb) | Comparaison des Solveurs de Sudoku | .NET (C#) | READY | BETA | 1h | po-2023 | +| 35 | [Sudoku-18-Comparison-CSharp.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-18-Comparison-CSharp.ipynb) | Comparaison des Solveurs de Sudoku | .NET (C#) | READY | BETA | 1h | po-2023 | | 36 | [Sudoku-18-Comparison-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-18-Comparison-Python.ipynb) | Comparaison des Solveurs de Sudoku | Python 3 | READY | BETA | 45min | po-2023 | | 37 | [Sudoku-18b-Statistical-Comparison-Python.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-18b-Statistical-Comparison-Python.ipynb) | Sudoku-18b - Comparaison statistique honnête de… | Python 3 | READY | BETA | 30min | po-2023 | -| 38 | [Sudoku-19-Lean-Propagation.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-19-Lean-Propagation.ipynb) | Sudoku-19 — Soundness de la propagation de… | Lean 4 (WSL) | READY | BETA | 15min | po-2023 | +| 38 | [Sudoku-19-Lean-Propagation-Lean.ipynb](MyIA.AI.Notebooks/Sudoku/Sudoku-19-Lean-Propagation-Lean.ipynb) | Sudoku-19 — Soundness de la propagation de… | Lean 4 (WSL) | READY | BETA | 15min | po-2023 | -### Probas (74 notebooks) — READY:74 | ALPHA:1, BETA:73 +### Probas (76 notebooks) — READY:76 | ALPHA:2, BETA:73, DRAFT:1 -#### Applications (3) +#### Applications (4) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| | 1 | [Percolation-Lean.ipynb](MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-Lean.ipynb) | Percolation-Lean — le noyau fini de percolation,… | Lean 4 (WSL, percolation) | READY | BETA | 30min | po-2023 | | 2 | [Percolation-Supercritique.ipynb](MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-Supercritique.ipynb) | Percolation supercritique : le géant au-dessus du… | Python 3 | READY | ALPHA | 30min | po-2023 | | 3 | [Pyro_RSA_Hyperbole.ipynb](MyIA.AI.Notebooks/Probas/Applications/Pyro_RSA_Hyperbole.ipynb) | Le Framework Rational Speech Act (RSA) | Python 3 | READY | BETA | 45min | po-2023 | +| 4 | [Quotients-Fibres-Recollement-Python.ipynb](MyIA.AI.Notebooks/Probas/Applications/Quotients-Fibres-Recollement-Python.ipynb) | Quotients, fibres et recollement : ce qui survit à… | Python 3 | READY | BETA | 30min | po-2023 | #### DecisionTheory (31) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| | 1 | [CausalBridges-01-Do-Calculus.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-01-Do-Calculus.ipynb) | Du graphe causal au do-calculus — le pont entre… | Python 3 (coursia-ml-training) | READY | BETA | 45min | po-2023 | -| 2 | [CausalBridges-02-Dowhy-Estimand-Intervention.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-02-Dowhy-Estimand-Intervention.ipynb) | DoWhy-1 — Exiger un estimand : l'identification… | Python 3 | READY | BETA | 30min | po-2023 | -| 3 | [CausalBridges-03-Dowhy-Contrefactuel-Individuel.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-03-Dowhy-Contrefactuel-Individuel.ipynb) | DoWhy-2 — Le contrefactuel individuel : quand… | Python 3 (coursia-ml-training) | READY | BETA | 30min | po-2023 | -| 4 | [CausalBridges-04-Dowhy-Decouverte-Structure.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-04-Dowhy-Decouverte-Structure.ipynb) | DoWhy-3 — La découverte de structure : le graphe… | Python (coursia-ml-training) | READY | BETA | 30min | po-2023 | -| 5 | [CausalBridges-05-Dowhy-Sensibilite-Confounder.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-05-Dowhy-Sensibilite-Confounder.ipynb) | DoWhy-4 — Le confondeur non observé : sensibilité,… | Python 3 (coursia-ml-training) | READY | BETA | 45min | po-2023 | -| 6 | [CausalBridges-06-Dowhy-Instrument-Faible.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-06-Dowhy-Instrument-Faible.ipynb) | DoWhy-5 — L'instrument faible : quand le pipeline… | Python (coursia-ml-training) | READY | BETA | 30min | po-2023 | +| 2 | [CausalBridges-02-Dowhy-Estimand-Intervention.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-02-Dowhy-Estimand-Intervention.ipynb) | CausalBridges-02 — Exiger un estimand :… | Python 3 | READY | BETA | 30min | po-2023 | +| 3 | [CausalBridges-03-Dowhy-Contrefactuel-Individuel.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-03-Dowhy-Contrefactuel-Individuel.ipynb) | CausalBridges-03 — Le contrefactuel individuel :… | Python 3 (coursia-ml-training) | READY | BETA | 30min | po-2023 | +| 4 | [CausalBridges-04-Dowhy-Decouverte-Structure.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-04-Dowhy-Decouverte-Structure.ipynb) | CausalBridges-04 — La découverte de structure : le… | Python (coursia-ml-training) | READY | BETA | 30min | po-2023 | +| 5 | [CausalBridges-05-Dowhy-Sensibilite-Confounder.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-05-Dowhy-Sensibilite-Confounder.ipynb) | CausalBridges-05 — Le confondeur non observé :… | Python 3 (coursia-ml-training) | READY | BETA | 45min | po-2023 | +| 6 | [CausalBridges-06-Dowhy-Instrument-Faible.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-06-Dowhy-Instrument-Faible.ipynb) | CausalBridges-06 — L'instrument faible : quand le… | Python (coursia-ml-training) | READY | BETA | 30min | po-2023 | | 7 | [CausalBridges-07-Quasi-Experimental.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-07-Quasi-Experimental.ipynb) | Méthodes quasi-expérimentales — identifier l'effet… | Python 3 (coursia-ml-training) | READY | BETA | 45min | po-2023 | | 8 | [CausalBridges-08-Causal-Fairness.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-08-Causal-Fairness.ipynb) | Causal-Fairness — Décomposer la discrimination :… | Python 3 (coursia-ml-training) | READY | BETA | 30min | po-2023 | | 9 | [DecInfer-01-Utility-Foundations.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-01-Utility-Foundations.ipynb) | DecInfer-01-Utility-Foundations : Axiomes et… | .NET (C#) | READY | BETA | 45min | po-2023 | @@ -1407,7 +1431,7 @@ Total notebooks: 1312 | 15 | [DecInfer-06-Value-Information.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-06-Value-Information.ipynb) | DecInfer-06-Value-Information : Valeur de… | .NET (C#) | READY | BETA | 45min | po-2023 | | 16 | [DecInfer-07-Expert-Systems.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-07-Expert-Systems.ipynb) | DecInfer-07-Expert-Systems : Decisions Robustes et… | .NET (C#) | READY | BETA | 45min | po-2023 | | 17 | [DecInfer-08-Sequential.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-08-Sequential.ipynb) | DecInfer-08-Sequential : MDPs, Bandits et POMDPs | .NET (C#) | READY | BETA | 45min | po-2023 | -| 18 | [DecInfer-09-Lean-Gittins.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-09-Lean-Gittins.ipynb) | DecInfer-09-Preuves formelles — Indice de Gittins | Lean 4 (WSL) | READY | BETA | 30min | po-2023 | +| 18 | [DecInfer-08b-Lean-Gittins.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-08b-Lean-Gittins.ipynb) | DecInfer-08b-Preuves formelles — Indice de Gittins | Lean 4 (WSL) | READY | BETA | 30min | po-2023 | | 19 | [DecInfer-10-Thompson-Sampling.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-10-Thompson-Sampling.ipynb) | DecInfer-10-Thompson-Sampling : Bandits bayesiens… | .NET (C#) | READY | BETA | 45min | po-2023 | | 20 | [DecPyMC-1-Utility-Foundations.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-1-Utility-Foundations.ipynb) | DecPyMC-1-Utility-Foundations : Axiomes et… | Python 3 | READY | BETA | 30min | po-2023 | | 21 | [DecPyMC-10-Ruine-Lundberg.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-10-Ruine-Lundberg.ipynb) | DecPyMC-10 : Ruine et capital — le processus de… | Python 3 (ipykernel) | READY | BETA | 30min | po-2023 | @@ -1416,7 +1440,7 @@ Total notebooks: 1312 | 24 | [DecPyMC-2-Utility-Money.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-2-Utility-Money.ipynb) | DecPyMC-2-Utility-Money : Utilite de l'Argent et… | Python 3 (ipykernel) | READY | BETA | 45min | po-2023 | | 25 | [DecPyMC-3-Multi-Attribute.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-3-Multi-Attribute.ipynb) | DecPyMC-3-Multi-Attribute : Utilite… | Python 3 | READY | BETA | 45min | po-2023 | | 26 | [DecPyMC-4-Decision-Networks.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-4-Decision-Networks.ipynb) | DecPyMC-4-Decision-Networks : Reseaux de Decision | Python 3 | READY | BETA | 30min | po-2023 | -| 27 | [DecPyMC-5-Value-Information.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-5-Value-Information.ipynb) | DecPyMC-5-Valeur de l'Information | Python 3 | READY | BETA | 1h | po-2023 | +| 27 | [DecPyMC-5-Value-Information.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-5-Value-Information.ipynb) | DecPyMC-5-Valeur de l'Information | Python 3 | READY | ALPHA | 1h | po-2023 | | 28 | [DecPyMC-6-Expert-Systems.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-6-Expert-Systems.ipynb) | DecPyMC-6-Systèmes Experts et Decisions Robustes | Python 3 | READY | BETA | 45min | po-2023 | | 29 | [DecPyMC-7-Sequential.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-7-Sequential.ipynb) | DecPyMC-7-MDPs, Bandits et POMDPs | Python 3 | READY | BETA | 45min | po-2023 | | 30 | [DecPyMC-8-Actuarial-Credibility.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-8-Actuarial-Credibility.ipynb) | DecPyMC-8 — Crédibilité actuarielle de… | Python 3 (ipykernel) | READY | BETA | 30min | po-2023 | @@ -1426,20 +1450,20 @@ Total notebooks: 1312 | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| -| 1 | [Infer-1-Setup.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-1-Setup.ipynb) | Infer-1-Setup : Introduction et Installation | .NET (C#) | READY | BETA | 45min | po-2023 | -| 2 | [Infer-10-Model-Selection.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-10-Model-Selection.ipynb) | Infer-10-Model-Sélection : Sélection et… | .NET (C#) | READY | BETA | 45min | po-2023 | -| 3 | [Infer-11-Topic-Models.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-11-Topic-Models.ipynb) | Infer-11-Topic-Models : Latent Dirichlet… | .NET (C#) | READY | BETA | 1h | po-2023 | -| 4 | [Infer-12-Modeles-Hierarchiques.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-12-Modeles-Hierarchiques.ipynb) | 12. Modèles Hiérarchiques Bayésiens — Pooling… | .NET (C#) | READY | BETA | 30min | po-2023 | -| 5 | [Infer-13-Crowdsourcing.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-13-Crowdsourcing.ipynb) | Infer-13-Crowdsourcing : Agregation de Labels et… | .NET (C#) | READY | BETA | 45min | po-2023 | -| 6 | [Infer-14-Sequences.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-14-Sequences.ipynb) | Infer-14-Sequences : Hidden Markov Models et… | .NET (C#) | READY | BETA | 1h | po-2023 | -| 7 | [Infer-15-Recommenders.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-15-Recommenders.ipynb) | Infer-15-Recommenders : systèmes de Recommandation | .NET (C#) | READY | BETA | 1h30 | po-2023 | -| 8 | [Infer-16-Sparse-Gaussian-Process.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-16-Sparse-Gaussian-Process.ipynb) | Infer-16-Sparse-Gaussian-Process : Processus… | .NET (C#) | READY | BETA | 45min | po-2023 | -| 9 | [Infer-17-Kalman-Filter.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-17-Kalman-Filter.ipynb) | Infer-17 — Filtre de Kalman : systèmes dynamiques… | .NET (C#) | READY | BETA | 30min | po-2023 | -| 10 | [Infer-18-Change-Point.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-18-Change-Point.ipynb) | Infer-18 — Détection de Rupture (Change-Point) :… | .NET (C#) | READY | BETA | 30min | po-2023 | -| 11 | [Infer-19-Survival-Analysis.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-19-Survival-Analysis.ipynb) | Infer-19 — Analyse de survie / fiabilite… | .NET (C#) | READY | BETA | 45min | po-2023 | -| 12 | [Infer-1b-Premiers-Modeles.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-1b-Premiers-Modeles.ipynb) | Infer-1b : Introduction a Infer.NET | .NET (C#) | READY | BETA | 1h | po-2023 | -| 13 | [Infer-2-Gaussian-Mixtures.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-2-Gaussian-Mixtures.ipynb) | Infer-2-Gaussian-Mixtures : Distributions… | .NET (C#) | READY | BETA | 1h | po-2023 | -| 14 | [Infer-20-Quotients-et-Fibres.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-20-Quotients-et-Fibres.ipynb) | Infer-20 — Quotients, fibres et recollement : ce… | Python 3 | READY | BETA | 30min | po-2023 | +| 1 | [Infer-08b-TrueSkill-Formules-Fermees-CSharp.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-08b-TrueSkill-Formules-Fermees-CSharp.ipynb) | Infer-8b-TrueSkill-Formules-Fermees : la mise a… | .NET (C#) | READY | BETA | 30min | po-2023 | +| 2 | [Infer-1-Setup.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-1-Setup.ipynb) | Infer-1-Setup : Introduction et Installation | .NET (C#) | READY | BETA | 45min | po-2023 | +| 3 | [Infer-10-Model-Selection.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-10-Model-Selection.ipynb) | Infer-10-Model-Sélection : Sélection et… | .NET (C#) | READY | BETA | 45min | po-2023 | +| 4 | [Infer-11-Topic-Models.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-11-Topic-Models.ipynb) | Infer-11-Topic-Models : Latent Dirichlet… | .NET (C#) | READY | BETA | 1h | po-2023 | +| 5 | [Infer-12-Modeles-Hierarchiques.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-12-Modeles-Hierarchiques.ipynb) | 12. Modèles Hiérarchiques Bayésiens — Pooling… | .NET (C#) | READY | BETA | 30min | po-2023 | +| 6 | [Infer-13-Crowdsourcing.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-13-Crowdsourcing.ipynb) | Infer-13-Crowdsourcing : Agregation de Labels et… | .NET (C#) | READY | BETA | 45min | po-2023 | +| 7 | [Infer-14-Sequences.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-14-Sequences.ipynb) | Infer-14-Sequences : Hidden Markov Models et… | .NET (C#) | READY | BETA | 1h | po-2023 | +| 8 | [Infer-15-Recommenders.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-15-Recommenders.ipynb) | Infer-15-Recommenders : systèmes de Recommandation | .NET (C#) | READY | BETA | 1h30 | po-2023 | +| 9 | [Infer-16-Sparse-Gaussian-Process.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-16-Sparse-Gaussian-Process.ipynb) | Infer-16-Sparse-Gaussian-Process : Processus… | .NET (C#) | READY | BETA | 45min | po-2023 | +| 10 | [Infer-17-Kalman-Filter.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-17-Kalman-Filter.ipynb) | Infer-17 — Filtre de Kalman : systèmes dynamiques… | .NET (C#) | READY | BETA | 30min | po-2023 | +| 11 | [Infer-18-Change-Point.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-18-Change-Point.ipynb) | Infer-18 — Détection de Rupture (Change-Point) :… | .NET (C#) | READY | BETA | 30min | po-2023 | +| 12 | [Infer-19-Survival-Analysis.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-19-Survival-Analysis.ipynb) | Infer-19 — Analyse de survie / fiabilite… | .NET (C#) | READY | BETA | 45min | po-2023 | +| 13 | [Infer-1b-Premiers-Modeles.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-1b-Premiers-Modeles.ipynb) | Infer-1b : Introduction a Infer.NET | .NET (C#) | READY | BETA | 1h | po-2023 | +| 14 | [Infer-2-Gaussian-Mixtures.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-2-Gaussian-Mixtures.ipynb) | Infer-2-Gaussian-Mixtures : Distributions… | .NET (C#) | READY | BETA | 1h | po-2023 | | 15 | [Infer-2b-Debugging-Bonnes-Pratiques.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-2b-Debugging-Bonnes-Pratiques.ipynb) | Infer-2b-Debugging-Bonnes-Pratiques :… | .NET (C#) | READY | BETA | 45min | po-2023 | | 16 | [Infer-3-Factor-Graphs.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-3-Factor-Graphs.ipynb) | Infer-3-Factor-Graphs : Graphes de Facteurs et… | .NET (C#) | READY | BETA | 45min | po-2023 | | 17 | [Infer-4-Bayesian-Networks.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-4-Bayesian-Networks.ipynb) | Infer-4-Bayesian-Networks : Reseaux Bayesiens… | .NET (C#) | READY | BETA | 1h | po-2023 | @@ -1448,7 +1472,7 @@ Total notebooks: 1312 | 20 | [Infer-8-TrueSkill.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-8-TrueSkill.ipynb) | Infer-8-TrueSkill : Système de Classement et… | .NET (C#) | READY | BETA | 1h | po-2023 | | 21 | [Infer-9-Classification.ipynb](MyIA.AI.Notebooks/Probas/Infer/Infer-9-Classification.ipynb) | Infer-9-Classification : Classification Bayesienne | .NET (C#) | READY | BETA | 1h | po-2023 | -#### PyMC (19) +#### PyMC (20) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -1471,8 +1495,9 @@ Total notebooks: 1312 | 17 | [PyMC-17-Kalman-Filter.ipynb](MyIA.AI.Notebooks/Probas/PyMC/PyMC-17-Kalman-Filter.ipynb) | 17. Filtre de Kalman : systèmes dynamiques… | Python 3 | READY | BETA | 30min | po-2023 | | 18 | [PyMC-18-Change-Point.ipynb](MyIA.AI.Notebooks/Probas/PyMC/PyMC-18-Change-Point.ipynb) | 18. Detection de Rupture (Change-Point) : inferer… | Python 3 | READY | BETA | 30min | po-2023 | | 19 | [PyMC-19-Survival-Analysis.ipynb](MyIA.AI.Notebooks/Probas/PyMC/PyMC-19-Survival-Analysis.ipynb) | 19. Analyse de survie / fiabilite bayesienne :… | Python 3 | READY | BETA | 30min | po-2023 | +| 20 | [PyMC-Observabilite-OTel.ipynb](MyIA.AI.Notebooks/Probas/PyMC/PyMC-Observabilite-OTel.ipynb) | Observabilité OTel — instrumenter un modèle PyMC… | Python 3 | READY | DRAFT | 30min | po-2023 | -### IIT (90 notebooks) — DEMO:5, READY:85 | ALPHA:1, BETA:78, DRAFT:11 +### IIT (93 notebooks) — DEMO:5, READY:88 | ALPHA:1, BETA:80, DRAFT:12 #### Racine (6) @@ -1482,10 +1507,10 @@ Total notebooks: 1312 | 2 | [IIT-02-AdvancedTopics.ipynb](MyIA.AI.Notebooks/IIT/IIT-02-AdvancedTopics.ipynb) | IIT - Sujets Avances : Partitionnement,… | Python 3 (PyPhi/IIT) | READY | BETA | 45min | po-2025 | | 3 | [IIT-03-CoarseGrainingMacroPhi.ipynb](MyIA.AI.Notebooks/IIT/IIT-03-CoarseGrainingMacroPhi.ipynb) | IIT-3. Coarse-graining, blackboxing et l'échelle… | pyphi | READY | BETA | 30min | po-2025 | | 4 | [IIT-04-Le-Probleme-de-Frontiere.ipynb](MyIA.AI.Notebooks/IIT/IIT-04-Le-Probleme-de-Frontiere.ipynb) | IIT-4. Le problème de frontière — qui décide où… | Python 3 (PyPhi/IIT) | READY | BETA | 30min | po-2025 | -| 5 | [IIT-05-Lentilles-et-Dissociations.ipynb](MyIA.AI.Notebooks/IIT/IIT-05-Lentilles-et-Dissociations.ipynb) | IIT-5. Les lentilles de conscience comme bancs de… | unknown | READY | BETA | 15min | po-2025 | +| 5 | [IIT-05-Lentilles-et-Dissociations.ipynb](MyIA.AI.Notebooks/IIT/IIT-05-Lentilles-et-Dissociations.ipynb) | IIT-5. Les lentilles de conscience comme bancs de… | unknown | READY | BETA | 30min | po-2025 | | 6 | [IIT-06-L-Objet-qui-a-Mordu-IIT.ipynb](MyIA.AI.Notebooks/IIT/IIT-06-L-Objet-qui-a-Mordu-IIT.ipynb) | IIT-6. L'objet qui a mordu IIT — l'expander à Φ… | Python 3 (PyPhi/IIT) | READY | BETA | 45min | po-2025 | -#### ICT-Series (84) +#### ICT-Series (87) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -1498,83 +1523,86 @@ Total notebooks: 1312 | 7 | [ICT-07-ScaleFreeSignatures-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-07-ScaleFreeSignatures-Python.ipynb) | ICT-7 — Signatures *scale-free* & criticalite | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | | 8 | [ICT-08-AttractorLandscapesEWS-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-08-AttractorLandscapesEWS-Python.ipynb) | ICT-8 — Paysages d'attracteurs & signaux… | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | | 9 | [ICT-09-AgencyRegeneration-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-09-AgencyRegeneration-Python.ipynb) | ICT-9 — Agence & regeneration : *reparer sa forme,… | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | -| 10 | [ICT-10-CatastropheGrammar.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-10-CatastropheGrammar.ipynb) | ICT-10 — Grammaire des catastrophes : *l'obstacle… | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | -| 11 | [ICT-11-CausalAgencyProfiles.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-11-CausalAgencyProfiles.ipynb) | ICT-11 — Profils d'agence causale : à quelle… | Python 3 | READY | BETA | 30min | po-2025 | -| 12 | [ICT-12-ValenceFieldsAndAnimats.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-12-ValenceFieldsAndAnimats.ipynb) | ICT-12 — Champs de valence et animats : rôles… | Python 3 | READY | BETA | 30min | po-2025 | -| 13 | [ICT-12b-LearnedValence.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-12b-LearnedValence.ipynb) | ICT-12b — Valence APPRISE, transferable,… | Python 3 | READY | BETA | 30min | po-2025 | -| 14 | [ICT-12c-PregnanceAnimat.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-12c-PregnanceAnimat.ipynb) | ICT-12c — Animat prégnance/valence incarné : la… | Python 3 | READY | BETA | 30min | po-2025 | -| 15 | [ICT-12d-InhibitedActionAnimat.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-12d-InhibitedActionAnimat.ipynb) | ICT-12d — Animat inhibé (Laborit) :… | Python 3 | READY | BETA | 30min | po-2025 | -| 16 | [ICT-12e-Value-of-Information-Animat.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-12e-Value-of-Information-Animat.ipynb) | ICT-12e — Valeur de l'information pour l'animat… | Python 3 | READY | BETA | 30min | po-2025 | -| 17 | [ICT-13-AxelrodStrategicMorphodynamics.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-13-AxelrodStrategicMorphodynamics.ipynb) | ICT-13 — Morphodynamique stratégique : une… | Python 3 | READY | BETA | 45min | po-2025 | -| 18 | [ICT-13b-DecroisementDynamiqueObservable.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-13b-DecroisementDynamiqueObservable.ipynb) | ICT-13b — Décroisement dynamique × observable :… | Python 3 | READY | ALPHA | 30min | po-2025 | -| 19 | [ICT-14-FreeEnergySurprise.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-14-FreeEnergySurprise.ipynb) | ICT-14 — Énergie libre et surprise du représentant… | Python 3 | READY | BETA | 30min | po-2025 | -| 20 | [ICT-14b-ActiveInferenceEFE.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-14b-ActiveInferenceEFE.ipynb) | ICT-14b — Inférence active : l'expected free… | Python 3 | READY | DRAFT | 30min | po-2025 | -| 21 | [ICT-15-IntegratedComplexity.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15-IntegratedComplexity.ipynb) | ICT-15 — Integrated Complexity : convergence Φ / F… | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | -| 22 | [ICT-15b-SensitivityCanonicity.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15b-SensitivityCanonicity.ipynb) | ICT-15b -- Sensitivity Canonicity (Huang 2019… | Python 3 | READY | DRAFT | 45min | po-2025 | -| 23 | [ICT-15c-MetaProxyObstruction.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15c-MetaProxyObstruction.ipynb) | ICT-15c — Méta-proxy d'obstruction : structure des… | Python 3 | READY | BETA | 30min | po-2025 | -| 24 | [ICT-15d-CechObstruction.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15d-CechObstruction.ipynb) | ICT-15d — Cochaîne de Čech pondérée : obstruction… | Python 3 | READY | BETA | 30min | po-2025 | -| 25 | [ICT-15e-Bridge2-RecoverabilityAgency.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15e-Bridge2-RecoverabilityAgency.ipynb) | ICT-15e -- Bridge #2 : recouvrabilite *est*… | Python 3 | READY | BETA | 30min | po-2025 | -| 26 | [ICT-15f-Bridge1bis-DecoupledFamily.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15f-Bridge1bis-DecoupledFamily.ipynb) | ICT-15f -- Pont #1-bis : la famille decouplee… | Python 3 | READY | BETA | 30min | po-2025 | -| 27 | [ICT-15g-EmpiricalHuangExploitation.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15g-EmpiricalHuangExploitation.ipynb) | ICT-15g -- Exploitation empirique de la… | Python 3 | READY | DRAFT | 30min | po-2025 | -| 28 | [ICT-15h-Bridge1bis-AsymmetricFamily.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15h-Bridge1bis-AsymmetricFamily.ipynb) | ICT-15h -- Pont #1-bis (chantier 2/3) : le regime… | Python 3 | READY | BETA | 30min | po-2025 | -| 29 | [ICT-15i-Bridge1bis-2DLandscape.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15i-Bridge1bis-2DLandscape.ipynb) | ICT-15i -- Pont #1-bis : le paysage 2D anisotrope… | unknown | READY | BETA | 30min | po-2025 | -| 30 | [ICT-15j-NerveDiscriminant.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15j-NerveDiscriminant.ipynb) | ICT-15j — Discriminant Čech par nerf simplicial… | Python 3 | READY | BETA | 30min | po-2025 | -| 31 | [ICT-15k-RecollementMacroCells.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15k-RecollementMacroCells.ipynb) | ICT-15k — Recollement des macrocells : le quadtree… | Python 3 | READY | BETA | 30min | po-2025 | -| 32 | [ICT-15l-IndependanceGenerateur.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15l-IndependanceGenerateur.ipynb) | ICT-15l — Indépendance au générateur de nouveauté… | Python 3 | READY | BETA | 30min | po-2025 | -| 33 | [ICT-16-MDLTwoPartCode.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-16-MDLTwoPartCode.ipynb) | ICT-16 — MDL / code en deux parties et bosse… | Python 3 | READY | BETA | 30min | po-2025 | -| 34 | [ICT-17-EpsilonMachine.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-17-EpsilonMachine.ipynb) | ICT-17 -- Mecanique computationnelle… | Python 3 | READY | DRAFT | 30min | po-2025 | -| 35 | [ICT-17b-Grokking-CompressionProgress.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-17b-Grokking-CompressionProgress.ipynb) | ICT-17b — Grokking et compression-progress : la… | Python 3 | READY | BETA | 30min | po-2025 | -| 36 | [ICT-18-ArrowOfTimeReversibilization.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-18-ArrowOfTimeReversibilization.ipynb) | ICT-18 -- Fleche du temps et reversibilisation… | Python 3 | READY | BETA | 30min | po-2025 | -| 37 | [ICT-18b-ReversibilityBudget.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-18b-ReversibilityBudget.ipynb) | ICT-18b — Budget de réversibilité : la jambe « fin… | Python 3 | READY | BETA | 30min | po-2025 | -| 38 | [ICT-19-EnjeuBattery.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-19-EnjeuBattery.ipynb) | ICT-19 — La batterie de l'ENJEU : auto-maintien vs… | Python 3 | READY | BETA | 30min | po-2025 | -| 39 | [ICT-19b-EnjeuBattery-Raffinement.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-19b-EnjeuBattery-Raffinement.ipynb) | ICT-19b — Raffinement et résolution des stubs… | Python 3 | READY | BETA | 30min | po-2025 | -| 40 | [ICT-20-FeatureCatastrophes.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-20-FeatureCatastrophes.ipynb) | ICT-20 — FeatureCatastrophes : *calibration de… | Python 3 | READY | BETA | 30min | po-2025 | -| 41 | [ICT-21-SAETrajectoires.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-21-SAETrajectoires.ipynb) | ICT-21 — SAETrajectoires : le substrat S4 entre au… | Python 3 | READY | BETA | 1h | po-2025 | -| 42 | [ICT-21b-SAECalibration.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-21b-SAECalibration.ipynb) | ICT-21b-SAECalibration — que reconstruit… | Python 3 | READY | BETA | 45min | po-2025 | -| 43 | [ICT-21c-SAECatastrophes.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-21c-SAECatastrophes.ipynb) | ICT-21c-SAECatastrophes — forme et dynamique des… | Python 3 | READY | BETA | 45min | po-2025 | -| 44 | [ICT-22-LLMSubstrat.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-22-LLMSubstrat.ipynb) | ICT-22 — LLMSubstrat : le transformer comme… | Python 3 | READY | BETA | 30min | po-2025 | -| 45 | [ICT-22b-CausalInterventionEngine.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-22b-CausalInterventionEngine.ipynb) | ICT-22b -- Moteur d'intervention causal : operer,… | Python 3 | DEMO | BETA | 45min | po-2025 | -| 46 | [ICT-23-PersonaCatastrophe.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-23-PersonaCatastrophe.ipynb) | ICT-23 — PersonaCatastrophe : la fronce de Thom… | Python 3 | READY | BETA | 15min | po-2025 | -| 47 | [ICT-24-WorkspaceIgnition.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-24-WorkspaceIgnition.ipynb) | ICT-24 — WorkspaceIgnition : l'axe Global… | Python 3 | READY | BETA | 30min | po-2025 | -| 48 | [ICT-25-InoculationRL.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-25-InoculationRL.ipynb) | ICT-25 — InoculationRL : GRPO à récompense… | Python 3 | READY | BETA | 1h | po-2025 | -| 49 | [ICT-26-SignalingConvention.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-26-SignalingConvention.ipynb) | ICT-26 — Convention de signalisation (expérience… | Python 3 | READY | BETA | 30min | po-2025 | -| 50 | [ICT-27-SymbolInvention.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-27-SymbolInvention.ipynb) | ICT-27 — Invention de symboles (expérience B,… | Python 3 | READY | BETA | 30min | po-2025 | -| 51 | [ICT-28-CollectiveAdoption.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-28-CollectiveAdoption.ipynb) | ICT-28 — Adoption collective et seuil de… | Python 3 | READY | BETA | 30min | po-2025 | -| 52 | [ICT-29-ConceptInoculation.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-29-ConceptInoculation.ipynb) | ICT-29 — Inoculation d'un concept (expérience D,… | Python 3 | READY | DRAFT | 30min | po-2025 | -| 53 | [ICT-30-InhibitedInvention.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-30-InhibitedInvention.ipynb) | ICT-30 — Invention inhibée (expérience E, strate… | Python 3 | READY | BETA | 30min | po-2025 | -| 54 | [ICT-31-ContrasteTroisSubstrats.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-31-ContrasteTroisSubstrats.ipynb) | ICT-31 — Le contraste mesuré à trois substrats :… | Python 3 | READY | BETA | 30min | po-2025 | -| 55 | [ICT-32-StratificationCausaleLife.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-32-StratificationCausaleLife.ipynb) | ICT-32 — Stratification causale du Jeu de la Vie :… | Python 3 | READY | BETA | 30min | po-2025 | -| 56 | [ICT-33-SoupCollisions.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-33-SoupCollisions.ipynb) | ICT-33 — Ensembles ouverts : soupes, collisions,… | Python 3 | READY | BETA | 30min | po-2025 | -| 57 | [ICT-34-BancRecollementLectures.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-34-BancRecollementLectures.ipynb) | ICT-34 — Le banc de recollement des lectures :… | Python 3 | READY | BETA | 30min | po-2025 | -| 58 | [ICT-35-HumorCausalProbe-Pilot.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35-HumorCausalProbe-Pilot.ipynb) | ICT-35 -- HumorCausalProbe-Pilot : substrat HLS,… | Python 3 | DEMO | BETA | 45min | po-2025 | -| 59 | [ICT-35b-HumorCausalPairs-SAE.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35b-HumorCausalPairs-SAE.ipynb) | ICT-35b -- HumorCausalPairs-SAE : paires… | Python 3 | DEMO | BETA | 30min | po-2025 | -| 60 | [ICT-35c-HumorDepthProfile-SAE.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35c-HumorDepthProfile-SAE.ipynb) | ICT-35c -- HumorDepthProfile-SAE : le verdict… | Python 3 | READY | BETA | 30min | po-2025 | -| 61 | [ICT-35d-HumorTypologyBreakdown-SAE.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35d-HumorTypologyBreakdown-SAE.ipynb) | ICT-35d -- HumorTypologyBreakdown-SAE : le verdict… | Python 3 | DEMO | BETA | 30min | po-2025 | -| 62 | [ICT-36-FLens-FactoredGeometry.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-36-FLens-FactoredGeometry.ipynb) | ICT-36 — F-Lens : mode factored-geometry,… | Python 3 | READY | BETA | 30min | po-2025 | -| 63 | [ICT-37-FLens-BeliefState.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-37-FLens-BeliefState.ipynb) | ICT-37 - F-Lens : mode belief-state, probing… | Python 3 | READY | DRAFT | 30min | po-2025 | -| 64 | [ICT-38-SLens-SelfLocation.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-38-SLens-SelfLocation.ipynb) | ICT-38 — S-Lens : la représentation porte-t-elle… | unknown | READY | BETA | 45min | po-2025 | -| 65 | [ICT-39-CompositionRegards.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-39-CompositionRegards.ipynb) | ICT-39 — Composition de regards | Python 3 | READY | BETA | 30min | po-2025 | -| 66 | [ICT-40a-TriangulationCausale.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-40a-TriangulationCausale.ipynb) | ICT-40a — Triangulation causale : SAE x J-Lens x… | Python 3 | READY | DRAFT | 45min | po-2025 | -| 67 | [ICT-40b-AnalogCognitionWaves.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-40b-AnalogCognitionWaves.ipynb) | ICT-40b — Cognition analogique : les ondes… | Python 3 | READY | BETA | 30min | po-2025 | -| 68 | [ICT-41-SAE-GeometrieFeatures.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-41-SAE-GeometrieFeatures.ipynb) | Geometrie des features SAE : galaxy, atome, dense… | Python 3 | READY | BETA | 30min | po-2025 | -| 69 | [ICT-42-Crosscoder-Distillation.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-42-Crosscoder-Distillation.ipynb) | ICT-42 — Crosscoder : diffuser deux modèles,… | coursia-ml-training | READY | BETA | 45min | po-2025 | -| 70 | [ICT-42-InoculationBifurcation-Pilot.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-42-InoculationBifurcation-Pilot.ipynb) | ICT-42 — Inoculation et bifurcation… | Python 3 | READY | DRAFT | 30min | po-2025 | -| 71 | [ICT-43-Calibration-MultiEchelle.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-43-Calibration-MultiEchelle.ipynb) | ICT-43 — Calibration multi-échelle, Phase 0 :… | Python 3 | DEMO | DRAFT | 15min | po-2025 | +| 10 | [ICT-10-CatastropheGrammar-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-10-CatastropheGrammar-Python.ipynb) | ICT-10 — Grammaire des catastrophes : *l'obstacle… | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | +| 11 | [ICT-11-CausalAgencyProfiles-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-11-CausalAgencyProfiles-Python.ipynb) | ICT-11 — Profils d'agence causale : à quelle… | Python 3 | READY | BETA | 30min | po-2025 | +| 12 | [ICT-12-ValenceFieldsAndAnimats-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-12-ValenceFieldsAndAnimats-Python.ipynb) | ICT-12 — Champs de valence et animats : rôles… | Python 3 | READY | BETA | 30min | po-2025 | +| 13 | [ICT-12b-LearnedValence-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-12b-LearnedValence-Python.ipynb) | ICT-12b — Valence APPRISE, transferable,… | Python 3 | READY | BETA | 30min | po-2025 | +| 14 | [ICT-12c-PregnanceAnimat-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-12c-PregnanceAnimat-Python.ipynb) | ICT-12c — Animat prégnance/valence incarné : la… | Python 3 | READY | BETA | 30min | po-2025 | +| 15 | [ICT-12d-InhibitedActionAnimat-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-12d-InhibitedActionAnimat-Python.ipynb) | ICT-12d — Animat inhibé (Laborit) :… | Python 3 | READY | BETA | 30min | po-2025 | +| 16 | [ICT-12e-Value-of-Information-Animat-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-12e-Value-of-Information-Animat-Python.ipynb) | ICT-12e — Valeur de l'information pour l'animat… | Python 3 | READY | BETA | 30min | po-2025 | +| 17 | [ICT-13-AxelrodStrategicMorphodynamics-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-13-AxelrodStrategicMorphodynamics-Python.ipynb) | ICT-13 — Morphodynamique stratégique : une… | Python 3 | READY | BETA | 45min | po-2025 | +| 18 | [ICT-13b-DecroisementDynamiqueObservable-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-13b-DecroisementDynamiqueObservable-Python.ipynb) | ICT-13b — Décroisement dynamique × observable :… | Python 3 | READY | ALPHA | 30min | po-2025 | +| 19 | [ICT-14-FreeEnergySurprise-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-14-FreeEnergySurprise-Python.ipynb) | ICT-14 — Énergie libre et surprise du représentant… | Python 3 | READY | BETA | 30min | po-2025 | +| 20 | [ICT-14b-ActiveInferenceEFE-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-14b-ActiveInferenceEFE-Python.ipynb) | ICT-14b — Inférence active : l'expected free… | Python 3 | READY | DRAFT | 30min | po-2025 | +| 21 | [ICT-15-IntegratedComplexity-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15-IntegratedComplexity-Python.ipynb) | ICT-15 — Integrated Complexity : convergence Φ / F… | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | +| 22 | [ICT-15b-SensitivityCanonicity-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15b-SensitivityCanonicity-Python.ipynb) | ICT-15b -- Sensitivity Canonicity (Huang 2019… | Python 3 | READY | DRAFT | 45min | po-2025 | +| 23 | [ICT-15c-MetaProxyObstruction-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15c-MetaProxyObstruction-Python.ipynb) | ICT-15c — Méta-proxy d'obstruction : structure des… | Python 3 | READY | BETA | 30min | po-2025 | +| 24 | [ICT-15d-CechObstruction-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15d-CechObstruction-Python.ipynb) | ICT-15d — Cochaîne de Čech pondérée : obstruction… | Python 3 | READY | BETA | 30min | po-2025 | +| 25 | [ICT-15e-Bridge2-RecoverabilityAgency-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15e-Bridge2-RecoverabilityAgency-Python.ipynb) | ICT-15e -- Bridge #2 : recouvrabilite *est*… | Python 3 | READY | BETA | 30min | po-2025 | +| 26 | [ICT-15f-Bridge1bis-DecoupledFamily-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15f-Bridge1bis-DecoupledFamily-Python.ipynb) | ICT-15f -- Pont #1-bis : la famille decouplee… | Python 3 | READY | BETA | 30min | po-2025 | +| 27 | [ICT-15g-EmpiricalHuangExploitation-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15g-EmpiricalHuangExploitation-Python.ipynb) | ICT-15g -- Exploitation empirique de la… | Python 3 | READY | DRAFT | 30min | po-2025 | +| 28 | [ICT-15h-Bridge1bis-AsymmetricFamily-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15h-Bridge1bis-AsymmetricFamily-Python.ipynb) | ICT-15h -- Pont #1-bis (chantier 2/3) : le regime… | Python 3 | READY | BETA | 30min | po-2025 | +| 29 | [ICT-15i-Bridge1bis-2DLandscape-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15i-Bridge1bis-2DLandscape-Python.ipynb) | ICT-15i -- Pont #1-bis : le paysage 2D anisotrope… | unknown | READY | BETA | 30min | po-2025 | +| 30 | [ICT-15j-NerveDiscriminant-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15j-NerveDiscriminant-Python.ipynb) | ICT-15j — Discriminant Čech par nerf simplicial… | Python 3 | READY | BETA | 30min | po-2025 | +| 31 | [ICT-15k-RecollementMacroCells-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15k-RecollementMacroCells-Python.ipynb) | ICT-15k — Recollement des macrocells : le quadtree… | Python 3 | READY | BETA | 30min | po-2025 | +| 32 | [ICT-15l-IndependanceGenerateur-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-15l-IndependanceGenerateur-Python.ipynb) | ICT-15l — Indépendance au générateur de nouveauté… | Python 3 | READY | BETA | 30min | po-2025 | +| 33 | [ICT-16-MDLTwoPartCode-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-16-MDLTwoPartCode-Python.ipynb) | ICT-16 — MDL / code en deux parties et bosse… | Python 3 | READY | BETA | 30min | po-2025 | +| 34 | [ICT-17-EpsilonMachine-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-17-EpsilonMachine-Python.ipynb) | ICT-17 -- Mecanique computationnelle… | Python 3 | READY | DRAFT | 30min | po-2025 | +| 35 | [ICT-17b-Grokking-CompressionProgress-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-17b-Grokking-CompressionProgress-Python.ipynb) | ICT-17b — Grokking et compression-progress : la… | Python 3 | READY | BETA | 45min | po-2025 | +| 36 | [ICT-18-ArrowOfTimeReversibilization-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-18-ArrowOfTimeReversibilization-Python.ipynb) | ICT-18 -- Fleche du temps et reversibilisation… | Python 3 | READY | BETA | 30min | po-2025 | +| 37 | [ICT-18b-ReversibilityBudget-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-18b-ReversibilityBudget-Python.ipynb) | ICT-18b — Budget de réversibilité : la jambe « fin… | Python 3 | READY | BETA | 30min | po-2025 | +| 38 | [ICT-19-EnjeuBattery-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-19-EnjeuBattery-Python.ipynb) | ICT-19 — La batterie de l'ENJEU : auto-maintien vs… | Python 3 | READY | BETA | 30min | po-2025 | +| 39 | [ICT-19b-EnjeuBattery-Raffinement-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-19b-EnjeuBattery-Raffinement-Python.ipynb) | ICT-19b — Raffinement et résolution des stubs… | Python 3 | READY | BETA | 30min | po-2025 | +| 40 | [ICT-20-FeatureCatastrophes-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-20-FeatureCatastrophes-Python.ipynb) | ICT-20 — FeatureCatastrophes : *calibration de… | Python 3 | READY | BETA | 30min | po-2025 | +| 41 | [ICT-21-SAETrajectoires-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-21-SAETrajectoires-Python.ipynb) | ICT-21 — SAETrajectoires : le substrat S4 entre au… | Python 3 | READY | BETA | 1h | po-2025 | +| 42 | [ICT-21b-SAECalibration-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-21b-SAECalibration-Python.ipynb) | ICT-21b-SAECalibration-Python — que reconstruit… | Python 3 | READY | BETA | 45min | po-2025 | +| 43 | [ICT-21c-SAECatastrophes-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-21c-SAECatastrophes-Python.ipynb) | ICT-21c-SAECatastrophes-Python — forme et… | Python 3 | READY | BETA | 45min | po-2025 | +| 44 | [ICT-22-LLMSubstrat-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-22-LLMSubstrat-Python.ipynb) | ICT-22 — LLMSubstrat : le transformer comme… | Python 3 | READY | BETA | 30min | po-2025 | +| 45 | [ICT-22b-CausalInterventionEngine-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-22b-CausalInterventionEngine-Python.ipynb) | ICT-22b -- Moteur d'intervention causal : operer,… | Python 3 | DEMO | BETA | 45min | po-2025 | +| 46 | [ICT-23-PersonaCatastrophe-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-23-PersonaCatastrophe-Python.ipynb) | ICT-23 — PersonaCatastrophe : la fronce de Thom… | Python 3 | READY | BETA | 15min | po-2025 | +| 47 | [ICT-24-WorkspaceIgnition-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-24-WorkspaceIgnition-Python.ipynb) | ICT-24 — WorkspaceIgnition : l'axe Global… | Python 3 | READY | BETA | 30min | po-2025 | +| 48 | [ICT-25-InoculationRL-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-25-InoculationRL-Python.ipynb) | ICT-25 — InoculationRL : GRPO à récompense… | Python 3 | READY | BETA | 1h | po-2025 | +| 49 | [ICT-26-SignalingConvention-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-26-SignalingConvention-Python.ipynb) | ICT-26 — Convention de signalisation (expérience… | Python 3 | READY | BETA | 30min | po-2025 | +| 50 | [ICT-27-SymbolInvention-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-27-SymbolInvention-Python.ipynb) | ICT-27 — Invention de symboles (expérience B,… | Python 3 | READY | BETA | 30min | po-2025 | +| 51 | [ICT-28-CollectiveAdoption-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-28-CollectiveAdoption-Python.ipynb) | ICT-28 — Adoption collective et seuil de… | Python 3 | READY | BETA | 30min | po-2025 | +| 52 | [ICT-29-ConceptInoculation-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-29-ConceptInoculation-Python.ipynb) | ICT-29 — Inoculation d'un concept (expérience D,… | Python 3 | READY | DRAFT | 30min | po-2025 | +| 53 | [ICT-30-InhibitedInvention-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-30-InhibitedInvention-Python.ipynb) | ICT-30 — Invention inhibée (expérience E, strate… | Python 3 | READY | BETA | 30min | po-2025 | +| 54 | [ICT-31-ContrasteTroisSubstrats-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-31-ContrasteTroisSubstrats-Python.ipynb) | ICT-31 — Le contraste mesuré à trois substrats :… | Python 3 | READY | BETA | 30min | po-2025 | +| 55 | [ICT-32-StratificationCausaleLife-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-32-StratificationCausaleLife-Python.ipynb) | ICT-32 — Stratification causale du Jeu de la Vie :… | Python 3 | READY | BETA | 30min | po-2025 | +| 56 | [ICT-33-SoupCollisions-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-33-SoupCollisions-Python.ipynb) | ICT-33 — Ensembles ouverts : soupes, collisions,… | Python 3 | READY | BETA | 30min | po-2025 | +| 57 | [ICT-34-BancRecollementLectures-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-34-BancRecollementLectures-Python.ipynb) | ICT-34 — Le banc de recollement des lectures :… | Python 3 | READY | BETA | 30min | po-2025 | +| 58 | [ICT-35-HumorCausalProbe-Pilot-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35-HumorCausalProbe-Pilot-Python.ipynb) | ICT-35 -- HumorCausalProbe-Pilot : substrat HLS,… | Python 3 | DEMO | BETA | 45min | po-2025 | +| 59 | [ICT-35b-HumorCausalPairs-SAE-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35b-HumorCausalPairs-SAE-Python.ipynb) | ICT-35b -- HumorCausalPairs-SAE : paires… | Python 3 | DEMO | BETA | 30min | po-2025 | +| 60 | [ICT-35c-HumorDepthProfile-SAE-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35c-HumorDepthProfile-SAE-Python.ipynb) | ICT-35c -- HumorDepthProfile-SAE : le verdict… | Python 3 | READY | BETA | 30min | po-2025 | +| 61 | [ICT-35d-HumorTypologyBreakdown-SAE-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35d-HumorTypologyBreakdown-SAE-Python.ipynb) | ICT-35d -- HumorTypologyBreakdown-SAE : le verdict… | Python 3 | DEMO | BETA | 30min | po-2025 | +| 62 | [ICT-36-FLens-FactoredGeometry-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-36-FLens-FactoredGeometry-Python.ipynb) | ICT-36 — F-Lens : mode factored-geometry,… | Python 3 | READY | BETA | 45min | po-2025 | +| 63 | [ICT-37-FLens-BeliefState-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-37-FLens-BeliefState-Python.ipynb) | ICT-37 - F-Lens : mode belief-state, probing… | Python 3 | READY | DRAFT | 30min | po-2025 | +| 64 | [ICT-38-SLens-SelfLocation-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-38-SLens-SelfLocation-Python.ipynb) | ICT-38 — S-Lens : la représentation porte-t-elle… | unknown | READY | BETA | 45min | po-2025 | +| 65 | [ICT-39-CompositionRegards-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-39-CompositionRegards-Python.ipynb) | ICT-39 — Composition de regards | Python 3 | READY | BETA | 30min | po-2025 | +| 66 | [ICT-40a-TriangulationCausale-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-40a-TriangulationCausale-Python.ipynb) | ICT-40a — Triangulation causale : SAE x J-Lens x… | Python 3 | READY | DRAFT | 45min | po-2025 | +| 67 | [ICT-40b-AnalogCognitionWaves-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-40b-AnalogCognitionWaves-Python.ipynb) | ICT-40b — Cognition analogique : les ondes… | Python 3 | READY | BETA | 30min | po-2025 | +| 68 | [ICT-41-SAE-GeometrieFeatures-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-41-SAE-GeometrieFeatures-Python.ipynb) | Geometrie des features SAE : galaxy, atome, dense… | Python 3 | READY | BETA | 30min | po-2025 | +| 69 | [ICT-42-Crosscoder-Distillation-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-42-Crosscoder-Distillation-Python.ipynb) | ICT-42 — Crosscoder : diffuser deux modèles,… | coursia-ml-training | READY | BETA | 45min | po-2025 | +| 70 | [ICT-42-InoculationBifurcation-Pilot-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-42-InoculationBifurcation-Pilot-Python.ipynb) | ICT-42 — Inoculation et bifurcation… | Python 3 | READY | DRAFT | 30min | po-2025 | +| 71 | [ICT-43-Calibration-MultiEchelle-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-43-Calibration-MultiEchelle-Python.ipynb) | ICT-43 — Calibration multi-échelle, Phase 0 :… | Python 3 | DEMO | DRAFT | 15min | po-2025 | | 72 | [ICT-44-GeometryOfTruth-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-44-GeometryOfTruth-Python.ipynb) | ICT-44 — La géométrie de la vérité : une direction… | coursia-ml-training | READY | BETA | 45min | po-2025 | -| 73 | [ICT-Annexe-ProxyContextuality.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Annexe-ProxyContextuality.ipynb) | ICT — Annexe : la contextualité du zoo de proxys… | Python 3 | READY | BETA | 30min | po-2025 | -| 74 | [ICT-Argumentation-BeliefTrajectories.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-BeliefTrajectories.ipynb) | ICT — Substrat argumentation : trajectoires de… | Python 3 | READY | BETA | 45min | po-2025 | -| 75 | [ICT-Argumentation-QBFAcceptance.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-QBFAcceptance.ipynb) | Argumentation strate 6 — Acceptabilité QBF :… | Python 3 | READY | BETA | 30min | po-2025 | -| 76 | [ICT-Argumentation-TruthMaintenance.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-TruthMaintenance.ipynb) | ICT — Substrat argumentation : maintenance de la… | Python 3 | READY | BETA | 30min | po-2025 | -| 77 | [ICT-Dissociation-PhatSelfReference.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-PhatSelfReference.ipynb) | Boucle auto-referentielle p_hat (case 2 / Epic… | Python 3 | READY | BETA | 30min | po-2025 | -| 78 | [ICT-Dissociation-SaillancePregnance.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-SaillancePregnance.ipynb) | ICT -- Dissociation saillance / pregnance (case s… | Python 3 | READY | BETA | 30min | po-2025 | -| 79 | [ICT-Greffe2-EspaceAtteignable.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Greffe2-EspaceAtteignable.ipynb) | ICT-Greffe2 — Le quadruplet $(A, F, r, \\pi)$ :… | Python 3 | READY | DRAFT | 30min | po-2025 | -| 80 | [ICT-Greffe4-VoteOnChain.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Greffe4-VoteOnChain.ipynb) | ICT-Greffe4 — Le vote argumenté sur chaîne :… | Python 3 | READY | BETA | 30min | po-2025 | -| 81 | [ICT-Greffe5-AttributionCausale.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Greffe5-AttributionCausale.ipynb) | ICT-Greffe5 -- Attribution causale de… | Python 3 | READY | DRAFT | 30min | po-2025 | -| 82 | [ICT-Life-SubstratCertifie.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Life-SubstratCertifie.ipynb) | ICT-Life — Substrat de calibration certifié : le… | Python 3 | READY | BETA | 30min | po-2025 | -| 83 | [ICT-SAE-JLens-TeteATete.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-SAE-JLens-TeteATete.ipynb) | Tete-a-tete SAE <-> J-space -- les deux lentilles… | Python 3 | READY | BETA | 45min | po-2025 | -| 84 | [ICT-Synthese-CrossSubstrat.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Synthese-CrossSubstrat.ipynb) | ICT-Synthèse — un seul appareil de mesure, cinq… | Python 3 | READY | BETA | 45min | po-2025 | - -### RL (36 notebooks) — DEMO:3, READY:33 | ALPHA:3, BETA:31, DRAFT:2 +| 73 | [ICT-45-InoculationBifurcation-9B-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-45-InoculationBifurcation-9B-Python.ipynb) | ICT-45 — Inoculation et bifurcation : la troisième… | Python 3 | READY | DRAFT | 45min | po-2025 | +| 74 | [ICT-46-Strate7-FreeCoordinates-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-46-Strate7-FreeCoordinates-Python.ipynb) | ICT-46 — Strate 7 : freebits de second ordre, le… | Python 3 | READY | BETA | 30min | po-2025 | +| 75 | [ICT-Annexe-ProxyContextuality.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Annexe-ProxyContextuality.ipynb) | ICT — Annexe : la contextualité du zoo de proxys… | Python 3 | READY | BETA | 30min | po-2025 | +| 76 | [ICT-Argumentation-BeliefTrajectories.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-BeliefTrajectories.ipynb) | ICT — Substrat argumentation : trajectoires de… | Python 3 | READY | BETA | 45min | po-2025 | +| 77 | [ICT-Argumentation-QBFAcceptance.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-QBFAcceptance.ipynb) | Argumentation strate 6 — Acceptabilité QBF :… | Python 3 | READY | BETA | 30min | po-2025 | +| 78 | [ICT-Argumentation-TruthMaintenance.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-TruthMaintenance.ipynb) | ICT — Substrat argumentation : maintenance de la… | Python 3 | READY | BETA | 30min | po-2025 | +| 79 | [ICT-Dissociation-PhatSelfReference.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-PhatSelfReference.ipynb) | Boucle auto-referentielle p_hat (case 2 / Epic… | Python 3 | READY | BETA | 30min | po-2025 | +| 80 | [ICT-Dissociation-SaillancePregnance.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-SaillancePregnance.ipynb) | ICT -- Dissociation saillance / pregnance (case s… | Python 3 | READY | BETA | 30min | po-2025 | +| 81 | [ICT-Greffe2-EspaceAtteignable.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Greffe2-EspaceAtteignable.ipynb) | ICT-Greffe2 — Le quadruplet $(A, F, r, \\pi)$ :… | Python 3 | READY | DRAFT | 30min | po-2025 | +| 82 | [ICT-Greffe4-VoteOnChain.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Greffe4-VoteOnChain.ipynb) | ICT-Greffe4 — Le vote argumenté sur chaîne :… | Python 3 | READY | BETA | 30min | po-2025 | +| 83 | [ICT-Greffe5-AttributionCausale.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Greffe5-AttributionCausale.ipynb) | ICT-Greffe5 -- Attribution causale de… | Python 3 | READY | DRAFT | 30min | po-2025 | +| 84 | [ICT-Life-SubstratCertifie.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Life-SubstratCertifie.ipynb) | ICT-Life — Substrat de calibration certifié : le… | Python 3 | READY | BETA | 30min | po-2025 | +| 85 | [ICT-MUH-FibreTegmark.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-MUH-FibreTegmark.ipynb) | ICT-MUH — Le texte où Tegmark cite Schmidhuber :… | Python 3 | READY | BETA | 30min | po-2025 | +| 86 | [ICT-SAE-JLens-TeteATete.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-SAE-JLens-TeteATete.ipynb) | Tete-a-tete SAE <-> J-space -- les deux lentilles… | Python 3 | READY | BETA | 45min | po-2025 | +| 87 | [ICT-Synthese-CrossSubstrat.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Synthese-CrossSubstrat.ipynb) | ICT-Synthèse — un seul appareil de mesure, cinq… | Python 3 | READY | BETA | 45min | po-2025 | + +### RL (36 notebooks) — DEMO:3, READY:33 | ALPHA:2, BETA:32, DRAFT:2 #### Racine (36) @@ -1586,7 +1614,7 @@ Total notebooks: 1312 | 4 | [rl_12_distributional_rl.ipynb](MyIA.AI.Notebooks/RL/rl_12_distributional_rl.ipynb) | RL-12 : Distributional RL — C51 (Categorical DQN)… | Python 3 | READY | BETA | 45min | po-2025 | | 5 | [rl_13_curiosity_exploration.ipynb](MyIA.AI.Notebooks/RL/rl_13_curiosity_exploration.ipynb) | RL 13 - Exploration par curiosité : Random Network… | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | | 6 | [rl_14_hierarchical_rl.ipynb](MyIA.AI.Notebooks/RL/rl_14_hierarchical_rl.ipynb) | Hierarchical RL — l'Option framework de Sutton,… | Python 3 | READY | BETA | 45min | po-2025 | -| 7 | [rl_15_grpo_group_relative_policy.ipynb](MyIA.AI.Notebooks/RL/rl_15_grpo_group_relative_policy.ipynb) | RL-15 — GRPO (Group Relative Policy Optimization)… | Python 3 | DEMO | ALPHA | 45min | po-2025 | +| 7 | [rl_15_grpo_group_relative_policy.ipynb](MyIA.AI.Notebooks/RL/rl_15_grpo_group_relative_policy.ipynb) | RL-15 — GRPO (Group Relative Policy Optimization)… | Python 3 | DEMO | BETA | 45min | po-2025 | | 8 | [rl_16_dream_rsi.ipynb](MyIA.AI.Notebooks/RL/rl_16_dream_rsi.ipynb) | RL-16 : Dream-RSI — l'exploration comme code,… | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | | 9 | [rl_17_k_server_wfa.ipynb](MyIA.AI.Notebooks/RL/rl_17_k_server_wfa.ipynb) | RL 17 - k-server et work function : la conjecture… | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | | 10 | [rl_18_matroid_secretary.ipynb](MyIA.AI.Notebooks/RL/rl_18_matroid_secretary.ipynb) | RL 18 - Le secrétaire matroïdal : la conjecture… | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | @@ -1611,7 +1639,7 @@ Total notebooks: 1312 | 29 | [rlpt_0c_reward_hacking_case_study.ipynb](MyIA.AI.Notebooks/RL/rlpt_0c_reward_hacking_case_study.ipynb) | RL Post-Training — 0c : l'anatomie d'un hack qui… | Python (coursia-ml-training) | READY | BETA | 45min | po-2025 | | 30 | [rlpt_0d_reward_trainer_sota.ipynb](MyIA.AI.Notebooks/RL/rlpt_0d_reward_trainer_sota.ipynb) | RL Post-Training — 0d : le reward model à la sauce… | Python 3 | READY | DRAFT | 45min | po-2025 | | 31 | [rlpt_0e_trl_DPO_SOTA.ipynb](MyIA.AI.Notebooks/RL/rlpt_0e_trl_DPO_SOTA.ipynb) | RL Post-Training — 0e : DPO version SOTA —… | Python 3 | READY | DRAFT | 45min | po-2025 | -| 32 | [rlpt_0f_comparaison_GRPO_TRL_et_PPO_maison.ipynb](MyIA.AI.Notebooks/RL/rlpt_0f_comparaison_GRPO_TRL_et_PPO_maison.ipynb) | rlpt_0f — Le SOTA de l'alignement en ligne :… | Python 3 | READY | ALPHA | 30min | po-2025 | +| 32 | [rlpt_0f_comparaison_GRPO_TRL_et_PPO_maison.ipynb](MyIA.AI.Notebooks/RL/rlpt_0f_comparaison_GRPO_TRL_et_PPO_maison.ipynb) | rlpt_0f — Le SOTA de l'alignement en ligne :… | Python 3 | READY | ALPHA | 45min | po-2025 | | 33 | [rlpt_1_ppo_lm_rlhf.ipynb](MyIA.AI.Notebooks/RL/rlpt_1_ppo_lm_rlhf.ipynb) | RL Post-Training — 1 : PPO pour l'alignement d'un… | Python 3 | READY | BETA | 30min | po-2025 | | 34 | [rlpt_2_grpo_minimal.ipynb](MyIA.AI.Notebooks/RL/rlpt_2_grpo_minimal.ipynb) | RL Post-Training — 2 : GRPO minimal — alignement… | Python (coursia-ml-training) | READY | BETA | 45min | po-2025 | | 35 | [rlpt_3_reward_hacking.ipynb](MyIA.AI.Notebooks/RL/rlpt_3_reward_hacking.ipynb) | RL Post-Training — 3 : Reward hacking — anatomie… | Python (coursia-ml-training) | DEMO | BETA | 45min | po-2025 | @@ -1656,6 +1684,14 @@ Total notebooks: 1312 | 8 | [Complexity-05-AaronsonArkhipov-PermanenteBosonSampling.ipynb](MyIA.AI.Notebooks/Complexity/Complexity-05-AaronsonArkhipov-PermanenteBosonSampling.ipynb) | Complexity-05 — La permanente, frontière quantique… | Python 3 | READY | BETA | 30min | | | 9 | [Complexity-06-Aaronson-Dequantification-Stabilizer.ipynb](MyIA.AI.Notebooks/Complexity/Complexity-06-Aaronson-Dequantification-Stabilizer.ipynb) | Complexity-06 — Déquantifier les suprématies | Python 3 | READY | BETA | 30min | | +### Compression (1 notebooks) — READY:1 | BETA:1 + +#### Racine (1) + +| # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | +|---|----------|-------|--------|--------|----------|----------|-------| +| 1 | [Compression-01-ShannonFano-Prefixe-Python.ipynb](MyIA.AI.Notebooks/Compression/Compression-01-ShannonFano-Prefixe-Python.ipynb) | Compression-01 — Codes préfixes : de Shannon-Fano… | Python 3 | READY | BETA | 30min | | + ### NLP (5 notebooks) — READY:5 | BETA:5 #### Racine (5) @@ -1679,8 +1715,8 @@ Total notebooks: 1312 ## Requirements -- **API**: 189 notebooks -- **GPU**: 173 notebooks +- **API**: 191 notebooks +- **GPU**: 180 notebooks - **Cloud**: 119 notebooks -- **WSL**: 104 notebooks -- **Local**: 809 notebooks \ No newline at end of file +- **WSL**: 118 notebooks +- **Local**: 814 notebooks \ No newline at end of file diff --git a/MyIA.AI.Notebooks/GameTheory/README.md b/MyIA.AI.Notebooks/GameTheory/README.md index 5a0ebfacad..db8e3e63ad 100644 --- a/MyIA.AI.Notebooks/GameTheory/README.md +++ b/MyIA.AI.Notebooks/GameTheory/README.md @@ -6,7 +6,7 @@ series: GameTheory pedagogical_count: 109 breakdown: root=99, SocialChoice=10 -maturity: BETA=100, DRAFT=5, ALPHA=4 +maturity: BETA=100, ALPHA=5, DRAFT=4 --> La théorie des jeux est le langage mathématique de la stratégie. Elle modélise les situations où des agents rationnels prennent des décisions dont le résultat dépend des choix des autres : enchères, négociations, élections, poker, allocation de ressources. Cette tension entre coopération et compétition traverse l'économie, les sciences politiques et l'informatique (mécanismes de vote, contrats, réseaux), et le prix Nobel d'économie a récompensé des théoriciens des jeux à sept reprises entre 1994 et 2020. diff --git a/MyIA.AI.Notebooks/GenAI/FineTuning/README.md b/MyIA.AI.Notebooks/GenAI/FineTuning/README.md index 08bd877507..ca04b9dd96 100644 --- a/MyIA.AI.Notebooks/GenAI/FineTuning/README.md +++ b/MyIA.AI.Notebooks/GenAI/FineTuning/README.md @@ -2,9 +2,9 @@ [← GenAI](../README.md) | [↑ ..](../README.md) | [→ PostTraining](../PostTraining/README.md) diff --git a/MyIA.AI.Notebooks/GenAI/PostTraining/README.md b/MyIA.AI.Notebooks/GenAI/PostTraining/README.md index 0436863807..caf5df5e61 100644 --- a/MyIA.AI.Notebooks/GenAI/PostTraining/README.md +++ b/MyIA.AI.Notebooks/GenAI/PostTraining/README.md @@ -6,7 +6,7 @@ series: GenAI-PostTraining pedagogical_count: 20 breakdown: PostTraining=20 -maturity: BETA=13, ALPHA=7 +maturity: BETA=14, ALPHA=6 --> > **Place dans GenAI** : cette série est le pendant *théorique et SOTA 2024-2025* de la série [FineTuning](../FineTuning/README.md). FineTuning couvre la boîte à outils pratique (LoRA, QLoRA, SFT, DPO, model merging) ; PostTraining remonte la chaîne conceptuelle complète SFT → RLHF → DPO → GRPO → RLVR → **GAE** et reproduit les techniques récentes (Deepseek-R1) sur petits modèles, complétée par un notebook d'évaluation comparative, un détecteur de reward hacking, et un notebook d'implémentation from-scratch de la famille "no critic" (GRPO/RLOO/GAE) sur toy env CPU, par un **notebook multi-step à crédit différé causal** (PT-12 : les cinq estimateurs re-mesurés, GAE-λ devient discriminant, verdict BEATS 5/5 seeds — le "1-step collapse" était une propriété du banc), et de **trois notebooks appliqués Qwen + GRPO + reward vérifiable + rewardspy en ligne** (PT-11a Z3 CSP arithmétique sur Qwen3.5-0.8B + PT-11b SymPy arithmétique + Z3 N-queens, plus leur validation multi-seed, **plus PT-11c sur le cran au-dessus Qwen3-1.7B/2B** qui qualifie l'étage GPU moyen 16 Go et oppose 0.8B vs 1.7B/2B à budget steps égal) qui font sortir la série du toy env vers un vrai LLM, et **PT-13 sur les corrections 2025 de la loss GRPO** (`Dr. GRPO` : retrait de `÷|o_i|` et `÷std` ; `clip-higher` de `DAPO` : ε_high=0.28 > ε_low=0.2), dont le biais de longueur est mesuré au **niveau gradient**, et **PT-14 sur les lois thermodynamiques de l'entraînement** (R08 : T ∼ η, équipartition ℓf = C·η, schedule 1/t optimal avec discontinuité η/2, force entropique — la physique des learning-rate schedules utilisés en PT-11), et **PT-15 sur le contrôle par interprétabilité** (R14 §3.2 / R11 §1.1 : refusal direction d'Arditi — extraction diffmoy, ablation par projection toutes-couches, steering additif ; machine unlearning et son évaluation white-box ; finetuning shallow « ~10 exemples rouvrent un modèle aligné » de Gade/Lermen ; evaluation awareness Claude 4.6/Apollo, et **PT-16 sur le vericoding** (Bursuc et al. 2025 : la preuve formelle comme récompense — pipeline spec → LLM local 7B → `Dafny verify`/`lean` réels → boucle de réparation 5 tentatives, avec le cas d'école LC0033 « liste vide prouvée conforme à une spec incomplète »), et **PT-17 sur les règles de score propres comme récompense (laya, Nandakishor M., Apache-2.0)** — récompense qui note une probabilité plutôt qu'une réponse ; étude étagée d'un modèle de décision non autorégressif (encodeur bidirectionnel + tête transformer, primitives `choice`/`score`/`noul`). Étage 1 (CPU from-scratch) : la famille des récompenses (binaire, linéaire, log, Brier, sphérique) sur tâche jouet où p(y|x) est connue — les propres **calibrent 7,6× mieux** que les impropres (ECE 0,011 vs 0,088) à exactitude comparable. Estimateur perturbation (GRPO-like G=8) vs gradient direct (MLE) : direct gagne en calibration. Question tranchée : la sur-confiance vient de **toute récompense qui ne note que l'argmax**, pas de la cross-entropie. Étage 2 (GPU 24 Go, ≥ 4 graines, bras CE / RL / RL+CE) reporté en PR séparée. Les deux se complèment : commencer par FineTuning pour la pratique, PostTraining pour la profondeur méthodologique. diff --git a/MyIA.AI.Notebooks/GenAI/README.md b/MyIA.AI.Notebooks/GenAI/README.md index f29ddd1f87..642ae6962a 100644 --- a/MyIA.AI.Notebooks/GenAI/README.md +++ b/MyIA.AI.Notebooks/GenAI/README.md @@ -418,7 +418,7 @@ Trois sous-dossiers complètent la série sans être des notebooks : diff --git a/MyIA.AI.Notebooks/GenAI/SemanticKernel/README.md b/MyIA.AI.Notebooks/GenAI/SemanticKernel/README.md index 119fa8b94f..6b12114b6e 100644 --- a/MyIA.AI.Notebooks/GenAI/SemanticKernel/README.md +++ b/MyIA.AI.Notebooks/GenAI/SemanticKernel/README.md @@ -2,9 +2,9 @@ [← Documentation GenAI](../README.md) | [↑ ..](../README.md) | [→ Génération de texte](../Texte/README.md) diff --git a/MyIA.AI.Notebooks/GenAI/Texte/README.md b/MyIA.AI.Notebooks/GenAI/Texte/README.md index 2f114c8d82..47c08b1bb9 100644 --- a/MyIA.AI.Notebooks/GenAI/Texte/README.md +++ b/MyIA.AI.Notebooks/GenAI/Texte/README.md @@ -2,9 +2,9 @@ [← Documentation GenAI](../README.md) | [↑ ..](../README.md) | [→ Semantic Kernel](../SemanticKernel/README.md) diff --git a/MyIA.AI.Notebooks/GenAI/Video/README.md b/MyIA.AI.Notebooks/GenAI/Video/README.md index ac17c24a33..012bc9af85 100644 --- a/MyIA.AI.Notebooks/GenAI/Video/README.md +++ b/MyIA.AI.Notebooks/GenAI/Video/README.md @@ -4,7 +4,7 @@ series: GenAI-Video pedagogical_count: 22 breakdown: Video=22 -maturity: BETA=18, ALPHA=4 +maturity: BETA=17, ALPHA=5 --> [← Documentation GenAI](../README.md) | [↑ ..](../README.md) | [→ Audio Sync](../Audio/04-Applications/04-4-Audio-Video-Sync.ipynb) diff --git a/MyIA.AI.Notebooks/IIT/ICT-Series/README.md b/MyIA.AI.Notebooks/IIT/ICT-Series/README.md index 859df60a5f..89a18fe6cc 100644 --- a/MyIA.AI.Notebooks/IIT/ICT-Series/README.md +++ b/MyIA.AI.Notebooks/IIT/ICT-Series/README.md @@ -2,9 +2,9 @@ [← IIT](../README.md) | [↑ Notebooks](../../README.md) | [→ Probas](../../Probas/README.md) diff --git a/MyIA.AI.Notebooks/IIT/README.md b/MyIA.AI.Notebooks/IIT/README.md index a39a483575..504751bfc6 100644 --- a/MyIA.AI.Notebooks/IIT/README.md +++ b/MyIA.AI.Notebooks/IIT/README.md @@ -497,7 +497,7 @@ Voir la licence du repository principal. \ No newline at end of file diff --git a/MyIA.AI.Notebooks/ML/README.md b/MyIA.AI.Notebooks/ML/README.md index 00b53dbda6..f3112f5dc7 100644 --- a/MyIA.AI.Notebooks/ML/README.md +++ b/MyIA.AI.Notebooks/ML/README.md @@ -2,9 +2,9 @@ > **À propos des décomptes** : le marqueur `CATALOG-STATUS` ci-dessus est la **source de vérité autoritative** pour les volumes (notebooks par sous-série, maturité). Il est régénéré chaque nuit par le workflow [`catalog-cron.yml`](../../.github/workflows/catalog-cron.yml) à 03:37 UTC sur `main` (commit `[skip ci]` par `github-actions[bot]`). Si vous observez un décalage entre ce marqueur et une phrase en prose de ce README — par exemple si une sous-série a reçu de nouveaux notebooks mergés après la dernière régénération —, **fiez-vous au marqueur** ; la prose sera ré-alignée manuellement lors du prochain passage. Pour les **décomptes par kernel** (Python vs C#/.NET) au sein d'une sous-série, ce README reste autoritatif car la décomposition langagière par sous-série n'est pas dans le marqueur agrégé. diff --git a/MyIA.AI.Notebooks/Probas/README.md b/MyIA.AI.Notebooks/Probas/README.md index 7ba9623868..acb76c7d8f 100644 --- a/MyIA.AI.Notebooks/Probas/README.md +++ b/MyIA.AI.Notebooks/Probas/README.md @@ -2,9 +2,9 @@ > **À propos des décomptes** : le marqueur `CATALOG-STATUS` ci-dessus est la **source de vérité autoritative** pour les volumes (notebooks par sous-série, maturité). Il est régénéré chaque nuit par le workflow [`catalog-cron.yml`](../../.github/workflows/catalog-cron.yml) à 03:37 UTC sur `main` (commit par `github-actions[bot]`, livré par la PR permanente `chore/catalog-refresh-pending`). Pour les **décomptes par kernel** (C#/.NET vs Python vs Lean 4) au sein d'une sous-série — c'est-à-dire la répartition **technique** par interpréteur —, ce README reste autoritatif car la décomposition langagière par sous-série n'est pas dans le marqueur agrégé ; cette granularité est documentée ici par lecture directe des `metadata.kernelspec.language` des notebooks (`28 C# + 41 Python + 3 Lean 4 = 72 ✓` au 19/09/2026). Si vous observez un décalage entre ce marqueur et une phrase en prose de ce README, **fiez-vous au marqueur** ; la prose sera ré-alignée manuellement lors du prochain passage — sauf si le marqueur est lui-même en retard sur le disque (sa PR de régénération en attente de merge) : au 19/09/2026 c'est le cas, le marqueur affiche encore les comptes d'avant l'arrivée des notebooks DoWhy-3/4/5 (mergés les 12-14/09/2026) ; la prose ci-dessous est alors mesurée sur le disque et prend temporairement l'avance. diff --git a/MyIA.AI.Notebooks/QuantConnect/Python/README.md b/MyIA.AI.Notebooks/QuantConnect/Python/README.md index 73c7bb9e58..2820ee806e 100644 --- a/MyIA.AI.Notebooks/QuantConnect/Python/README.md +++ b/MyIA.AI.Notebooks/QuantConnect/Python/README.md @@ -2,7 +2,7 @@ series: QuantConnect-Python pedagogical_count: 60 breakdown: Python=60 -maturity: DRAFT=32, BETA=20, ALPHA=8 +maturity: DRAFT=33, BETA=19, ALPHA=8 --> # QuantConnect Python Notebooks diff --git a/MyIA.AI.Notebooks/QuantConnect/README.md b/MyIA.AI.Notebooks/QuantConnect/README.md index c95fdd9195..c39f44cd5b 100644 --- a/MyIA.AI.Notebooks/QuantConnect/README.md +++ b/MyIA.AI.Notebooks/QuantConnect/README.md @@ -4,7 +4,7 @@ series: QuantConnect pedagogical_count: 115 breakdown: Python=60, projects=49, ML-Training-Pipeline=4, kelly_lean=2 -maturity: BETA=65, DRAFT=37, ALPHA=12, TEMPLATE=1 +maturity: BETA=64, DRAFT=38, ALPHA=12, TEMPLATE=1 --> > **Note éditoriale — counts kernels par sous-série** : Le marqueur CATALOG-STATUS agrégé ci-dessus reste **autoritatif** pour la décomposition par **sous-série** (Python / projects / ML-Training-Pipeline / kelly_lean). En revanche, pour les décomptes par **kernel** (Python vs Lean 4) **au sein** d'une sous-série — c'est-à-dire la répartition technique par interpréteur —, **ce README reste autoritatif** car la décomposition langagière par sous-série n'est pas dans le marqueur agrégé. Cette granularité est documentée ici par lecture directe des `metadata.kernelspec.language` des notebooks : diff --git a/MyIA.AI.Notebooks/README.md b/MyIA.AI.Notebooks/README.md index 386d50a0af..52fa4e86a0 100644 --- a/MyIA.AI.Notebooks/README.md +++ b/MyIA.AI.Notebooks/README.md @@ -10,9 +10,9 @@ Le catalogue rassemble **plusieurs centaines de notebooks pédagogiques** répar *Marqueur auto-régénéré quotidiennement par `.github/workflows/catalog-cron.yml` (file [`COURSE_CATALOG.generated.md`](../COURSE_CATALOG.generated.md) — source de vérité sur les volumes et la maturité). Toute PR qui modifierait ce bloc est signalée par `catalog-drift.yml` (read-only, catalog-pr-hygiene R1).* diff --git a/MyIA.AI.Notebooks/RL/README.md b/MyIA.AI.Notebooks/RL/README.md index 15f53bf17d..9c6b10b3df 100644 --- a/MyIA.AI.Notebooks/RL/README.md +++ b/MyIA.AI.Notebooks/RL/README.md @@ -6,7 +6,7 @@ series: RL pedagogical_count: 36 breakdown: root=36 -maturity: BETA=31, ALPHA=3, DRAFT=2 +maturity: BETA=32, ALPHA=2, DRAFT=2 --> > **Note éditoriale (counts)** : Le marqueur `CATALOG-STATUS` ci-dessus est autoritatif pour le compte agrégé (26 notebooks pédagogiques). Pour la **décomposition langagière par kernel** (`metadata.kernelspec.language`), ce README reste autoritatif car la granularité kernel n'est pas dans le marqueur agrégé ; elle est documentée ici par lecture directe des kernelspecs au 23/09/2026 : diff --git a/MyIA.AI.Notebooks/Search/README.md b/MyIA.AI.Notebooks/Search/README.md index 45f4413c8a..a8f5ce62c3 100644 --- a/MyIA.AI.Notebooks/Search/README.md +++ b/MyIA.AI.Notebooks/Search/README.md @@ -2,9 +2,9 @@ [← Notebooks](../README.md) | [↑ ..](../README.md) | [→ SymbolicAI](../SymbolicAI/README.md) diff --git a/MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/README.md b/MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/README.md index 4078fff644..0e318fc951 100644 --- a/MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/README.md +++ b/MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/README.md @@ -2,9 +2,9 @@ [← SmartContracts](../SmartContracts/README.md) | [↑ SymbolicAI](../README.md) | [SymbolicLearning →](../SymbolicLearning/README.md) diff --git a/MyIA.AI.Notebooks/SymbolicAI/Lean/README.md b/MyIA.AI.Notebooks/SymbolicAI/Lean/README.md index f182a243db..be73ba46ad 100644 --- a/MyIA.AI.Notebooks/SymbolicAI/Lean/README.md +++ b/MyIA.AI.Notebooks/SymbolicAI/Lean/README.md @@ -2,9 +2,9 @@ [← SemanticWeb](../SemanticWeb/README.md) | [↑ SymbolicAI](../README.md) | [Planners →](../Planners/README.md) diff --git a/MyIA.AI.Notebooks/SymbolicAI/README.md b/MyIA.AI.Notebooks/SymbolicAI/README.md index 01ab7d33cd..e770d4fc20 100644 --- a/MyIA.AI.Notebooks/SymbolicAI/README.md +++ b/MyIA.AI.Notebooks/SymbolicAI/README.md @@ -4,9 +4,9 @@ L'intelligence artificielle n'est pas qu'apprentissage automatique et réseaux de neurones. Une grande partie de l'IA classique repose sur le **raisonnement symbolique** : représenter la connaissance sous forme de propositions, de règles et de structures logiques, puis dériver mécaniquement de nouvelles conclusions. C'est cette tradition — des systèmes experts des années 80 aux assistants de preuve modernes comme Lean 4 — que cette famille de séries explore. diff --git a/MyIA.AI.Notebooks/SymbolicAI/SMT/README.md b/MyIA.AI.Notebooks/SymbolicAI/SMT/README.md index 8a29549d75..9d11f3d5d1 100644 --- a/MyIA.AI.Notebooks/SymbolicAI/SMT/README.md +++ b/MyIA.AI.Notebooks/SymbolicAI/SMT/README.md @@ -1,8 +1,8 @@ # SMT - Satisfiability Modulo Theories diff --git a/MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/README.md b/MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/README.md index aef002f119..56f0d889f9 100644 --- a/MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/README.md +++ b/MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/README.md @@ -6,7 +6,7 @@ series: SymbolicAI-SemanticWeb pedagogical_count: 28 breakdown: SemanticWeb=28 -maturity: BETA=27, ALPHA=1 +maturity: BETA=26, ALPHA=2 --> Le Web Sémantique est la promesse d'un Web où les machines comprennent la signification des données, pas seulement leur syntaxe. RDF, SPARQL, OWL, SHACL : ces standards du W3C définissent un langage commun pour décrire, interroger, valider et raisonner sur des graphes de connaissances. Cette série vous mène des fondations (.NET C# avec dotNetRDF) aux applications modernes (Python avec rdflib, pySHACL, GraphRAG), en passant par les ontologies, les données liées et les standards émergents (RDF 1.2, JSON-LD 1.1). diff --git a/MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/README.md b/MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/README.md index 431bffb6a0..6f63b8d2a7 100644 --- a/MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/README.md +++ b/MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/README.md @@ -4,9 +4,9 @@ ## Présentation diff --git a/docs/archive/reference/HEALTH_DASHBOARD.md b/docs/archive/reference/HEALTH_DASHBOARD.md index 9038080823..1aa988436c 100644 --- a/docs/archive/reference/HEALTH_DASHBOARD.md +++ b/docs/archive/reference/HEALTH_DASHBOARD.md @@ -1,28 +1,28 @@ # Tableau de santé du dépôt — snapshot dérivé du catalogue -> Snapshot statique généré depuis `COURSE_CATALOG.generated.json` (date catalogue : **2026-09-27**). +> Snapshot statique généré depuis `COURSE_CATALOG.generated.json` (date catalogue : **2026-10-02**). > Ce fichier **n'est pas maintenu à la main** : il est dérivé du catalogue (acceptance #4 de #4210). > Pour le régénérer : `python scripts/notebook_tools/generate_health_dashboard.py`. -**1312** notebooks référencés au catalogue. +**1340** notebooks référencés au catalogue. ## État global | Statut | Count | % | |--------|-------|---| -| READY | 1111 | 84.7% | -| DEMO | 198 | 15.1% | -| BROKEN | 3 | 0.2% | +| READY | 1137 | 84.9% | +| DEMO | 201 | 15.0% | +| BROKEN | 2 | 0.1% | ## Exigences d'environnement (badges) | Exigence | Notebooks concernés | |----------|---------------------| -| **local** (exécutable sans GPU/cloud/WSL) | 809 | -| WSL requis | 104 | -| GPU requis | 173 | +| **local** (exécutable sans GPU/cloud/WSL) | 814 | +| WSL requis | 118 | +| GPU requis | 180 | | Cloud requis (QC / GenAI Docker) | 119 | -| API key requise | 189 | +| API key requise | 191 | ## Distribution par série @@ -30,65 +30,68 @@ |-------|-------|------|--------|-------|---------| | CaseStudies | 6 | 0 | 0 | 6 | 100% | | Complexity | 9 | 0 | 0 | 9 | 100% | -| GameTheory | 107 | 1 | 1 | 109 | 98% | -| GenAI | 124 | 121 | 2 | 247 | 50% | -| IIT | 85 | 5 | 0 | 90 | 94% | -| ML | 104 | 16 | 0 | 120 | 87% | +| Compression | 1 | 0 | 0 | 1 | 100% | +| GameTheory | 108 | 1 | 0 | 109 | 99% | +| GenAI | 131 | 124 | 2 | 257 | 51% | +| IIT | 88 | 5 | 0 | 93 | 95% | +| ML | 108 | 18 | 0 | 126 | 86% | | NLP | 5 | 0 | 0 | 5 | 100% | -| Probas | 74 | 0 | 0 | 74 | 100% | +| Probas | 76 | 0 | 0 | 76 | 100% | | QuantConnect | 71 | 44 | 0 | 115 | 62% | | RL | 33 | 3 | 0 | 36 | 92% | -| Search | 155 | 0 | 0 | 155 | 100% | +| Search | 156 | 0 | 0 | 156 | 100% | | Sudoku | 37 | 1 | 0 | 38 | 97% | -| SymbolicAI | 300 | 7 | 0 | 307 | 98% | +| SymbolicAI | 307 | 5 | 0 | 312 | 98% | | cross-series | 1 | 0 | 0 | 1 | 100% | ## Kernels | Kernel | Count | |--------|-------| -| Python 3 | 859 | -| .NET (C#) | 264 | -| Python 3 (ipykernel) | 48 | -| Lean 4 (WSL) | 47 | +| Python 3 | 879 | +| .NET (C#) | 265 | +| Python 3 (ipykernel) | 49 | +| Lean 4 (WSL) | 48 | | Python (coursia-ml-training) | 17 | -| Python 3 (coursia-ml-training) | 15 | +| Python 3 (coursia-ml-training) | 17 | | coursia-ml-training | 12 | -| Python 3 (WSL) | 7 | +| Python 3 (WSL) | 6 | | Python 3 (PyPhi/IIT) | 6 | | Coursia ML Training | 3 | | unknown | 3 | | Lean 4 | 3 | | Python (GameTheory WSL + OpenSpiel) | 2 | +| base | 2 | | Python 3 (coursia2) | 2 | | Python3 | 2 | | .venv | 2 | | Python 3 (venv projet) | 1 | | Lean (WSL) | 1 | | Python 3 (c820) | 1 | -| Python (CoursIA-2 venv) | 1 | +| .venv (3.12.14) | 1 | | Python (dia-tts) | 1 | | Python 3 (mert2-gpu) | 1 | | Python (sheetsage2-gpu) | 1 | | Python 3 (PyTorch) | 1 | | Python 3 (coursia-sae) | 1 | | pyphi | 1 | +| Python 3.11 (coursia-drift) | 1 | | Lean 4 (WSL, percolation) | 1 | | Foundation-Py-Default | 1 | | .venv (3.14.3) | 1 | -| Lean 4 (WSL, conway-build) | 1 | | Lean 4 (WSL, grothendieck-16200) | 1 | +| Python 3.13.x (CPython canonique serie Lean) | 1 | +| Lean 4 (WSL, conway-build) | 1 | | .venv (3.12.3) | 1 | | cours-ia | 1 | | Python 3 (SC-16 Concrete, WSL) | 1 | | Python 3 (smartcontracts) | 1 | | Python (difflogic-sl12) | 1 | -## BROKEN (3 — à traiter en priorité) +## BROKEN (2 — à traiter en priorité) | Série | Notebook | Maturité | Dernière validation | |-------|----------|----------|---------------------| -| GameTheory | GameTheory-06g — Agents à budget explicite (companion Lean natif) | DRAFT | 2026-09-21 | | GenAI | Notebook de travail | TEMPLATE | 2026-07-30 | | GenAI | Notebook de travail | TEMPLATE | 2026-07-30 | diff --git a/docs/curriculum/genai.md b/docs/curriculum/genai.md index 6ee4e5becf..f0927c571b 100644 --- a/docs/curriculum/genai.md +++ b/docs/curriculum/genai.md @@ -20,9 +20,9 @@ Génération d'images (DALL-E, Stable Diffusion, Qwen, ComfyUI), synthèse vocal | Métrique | Valeur | |----------|--------| -| Notebooks | 229 | +| Notebooks | 238 | | PRODUCTION | 0 | -| BETA | 208 | +| BETA | 217 | | ALPHA | 21 | ## GenAI/00-GenAI-Environment (6 notebooks) @@ -97,20 +97,21 @@ Génération d'images (DALL-E, Stable Diffusion, Qwen, ComfyUI), synthèse vocal | 4 | [04 — Matrice de couverture cross-notebooks](../../MyIA.AI.Notebooks/GenAI/FallacyDetection/04_coverage_matrix.ipynb) | BETA | Oui | | 5 | [05 — Constructeur du dataset de Phase 2 : produit…](../../MyIA.AI.Notebooks/GenAI/FallacyDetection/05_dataset_builder.ipynb) | BETA | Oui | -## GenAI/FineTuning (10 notebooks) +## GenAI/FineTuning (11 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| | 1 | [FT-00a : LoRA from scratch — démonter l'adaptation…](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-00a-LoRA-from-scratch-Python.ipynb) | BETA | Non | | 2 | [FT-00b : LoRA hyperparams from scratch — ablation rang…](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-00b-LoRA-Hyperparams-from-scratch-Python.ipynb) | BETA | Non | | 3 | [FT-00c : LoRA SOTA — la même adaptation, cette fois…](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-00c-LoRA-SOTA-Comparison-Python.ipynb) | BETA | Non | -| 4 | [FT-01 : Introduction au Fine-Tuning](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-01-Introduction-FineTuning-Python.ipynb) | BETA | Non | -| 5 | [FT-02 : QLoRA — Fine-Tuning avec Quantization](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-02-QLoRA-Quantization-Python.ipynb) | BETA | Non | -| 6 | [FT-03 : Supervised Fine-Tuning (SFT) — Enseigner un…](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-03-Supervised-FineTuning-SFT-Python.ipynb) | BETA | Non | -| 7 | [FT-04 : RLHF et Alignement — Préférences Humaines et…](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-04-RLHF-DPO-Python.ipynb) | BETA | Non | -| 8 | [FT-05 : Fusion et Routage de Modèles -- Combiner les…](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-05-ModelMerging-Routing-Python.ipynb) | BETA | Non | -| 9 | [FT-05: Model Merging and Routing -- Combining…](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-05-ModelMerging-Routing-Python_en.ipynb) | BETA | Non | -| 10 | [FT-06 : LoRA vision-langage — fine-tune du décodeur de…](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-06-Vision-Language-LoRA-Python.ipynb) | BETA | Non | +| 4 | [FT-00d : LoRA + QLoRA SOTA Comparison](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-00d-LoRA-QLoRA-SOTA-Comparison-Python.ipynb) | BETA | Non | +| 5 | [FT-01 : Introduction au Fine-Tuning](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-01-Introduction-FineTuning-Python.ipynb) | BETA | Non | +| 6 | [FT-02 : QLoRA — Fine-Tuning avec Quantization](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-02-QLoRA-Quantization-Python.ipynb) | BETA | Non | +| 7 | [FT-03 : Supervised Fine-Tuning (SFT) — Enseigner un…](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-03-Supervised-FineTuning-SFT-Python.ipynb) | BETA | Non | +| 8 | [FT-04 : RLHF et Alignement — Préférences Humaines et…](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-04-RLHF-DPO-Python.ipynb) | BETA | Non | +| 9 | [FT-05 : Fusion et Routage de Modèles -- Combiner les…](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-05-ModelMerging-Routing-Python.ipynb) | BETA | Non | +| 10 | [FT-05: Model Merging and Routing -- Combining…](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-05-ModelMerging-Routing-Python_en.ipynb) | BETA | Non | +| 11 | [FT-06 : LoRA vision-langage — fine-tune du décodeur de…](../../MyIA.AI.Notebooks/GenAI/FineTuning/FT-06-Vision-Language-LoRA-Python.ipynb) | BETA | Non | ## GenAI/Image (21 notebooks) @@ -203,7 +204,7 @@ Génération d'images (DALL-E, Stable Diffusion, Qwen, ComfyUI), synthèse vocal | 16 | [PT-13 — Les trois biais du loss GRPO et leurs…](../../MyIA.AI.Notebooks/GenAI/PostTraining/PT_13_dapo_drgrpo_corrections.ipynb) | ALPHA | Oui | | 17 | [PT-14 — Lois thermodynamiques de l'entraînement :…](../../MyIA.AI.Notebooks/GenAI/PostTraining/PT_14_neural_thermodynamic_laws.ipynb) | BETA | Oui | | 18 | [PT-15 — Contrôle par interprétabilité : refusal…](../../MyIA.AI.Notebooks/GenAI/PostTraining/PT_15_controle_interpretabilite.ipynb) | BETA | Non | -| 19 | [PT-16 — Vericoding : la preuve formelle comme…](../../MyIA.AI.Notebooks/GenAI/PostTraining/PT_16_vericoding_formal_verification.ipynb) | ALPHA | Oui | +| 19 | [PT-16 — Vericoding : la preuve formelle comme…](../../MyIA.AI.Notebooks/GenAI/PostTraining/PT_16_vericoding_formal_verification.ipynb) | BETA | Oui | | 20 | [PT-17 — laya : la règle de score propre comme…](../../MyIA.AI.Notebooks/GenAI/PostTraining/PT_17_laya_proper_rewards_toy.ipynb) | BETA | Non | ## GenAI/RAG-et-Memoire-Semantique (10 notebooks) @@ -221,7 +222,7 @@ Génération d'images (DALL-E, Stable Diffusion, Qwen, ComfyUI), synthèse vocal | 9 | [RAG 08 — Kernel Memory et la recherche hybride : BM25 +…](../../MyIA.AI.Notebooks/GenAI/RAG-et-Memoire-Semantique/08-KernelMemory-Hybrid-Search.ipynb) | BETA | Non | | 10 | [RAG 09 — Au-delà du texte : le plafond multimodal du…](../../MyIA.AI.Notebooks/GenAI/RAG-et-Memoire-Semantique/09-KernelMemory-Multimodal.ipynb) | BETA | Non | -## GenAI/Security (5 notebooks) +## GenAI/Security (6 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -230,8 +231,9 @@ Génération d'images (DALL-E, Stable Diffusion, Qwen, ComfyUI), synthèse vocal | 3 | [Oversight — Scaling Laws sur le jeu de Nim (R12,…](../../MyIA.AI.Notebooks/GenAI/Security/Oversight/Oversight-Scaling-Laws-Nim.ipynb) | BETA | Oui | | 4 | [Oversight-Scaling-Laws-Statistics](../../MyIA.AI.Notebooks/GenAI/Security/Oversight/Oversight-Scaling-Laws-Statistics.ipynb) | BETA | Oui | | 5 | [Oversight-Scaling-Laws-Wargames](../../MyIA.AI.Notebooks/GenAI/Security/Oversight/Oversight-Scaling-Laws-Wargames.ipynb) | BETA | Oui | +| 6 | [Surface d'attaque des outils MCP — le piège de la…](../../MyIA.AI.Notebooks/GenAI/Security/Tooling/Tooling-MCP-Attack-Surface.ipynb) | BETA | Non | -## GenAI/SemanticKernel (15 notebooks) +## GenAI/SemanticKernel (16 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -246,48 +248,55 @@ Génération d'images (DALL-E, Stable Diffusion, Qwen, ComfyUI), synthèse vocal | 9 | [SK-9-Building-CLR : Interoperabilite Python/.NET via…](../../MyIA.AI.Notebooks/GenAI/SemanticKernel/09-SemanticKernel-Building-CLR.ipynb) | BETA | Non | | 10 | [SK-10-NotebookMaker : Système Multi-Agents pour…](../../MyIA.AI.Notebooks/GenAI/SemanticKernel/10-SemanticKernel-NotebookMaker.ipynb) | BETA | Non | | 11 | [Conception Automatique de Notebook par Agents IA](../../MyIA.AI.Notebooks/GenAI/SemanticKernel/10b-SemanticKernel-NotebookMaker-batch-parameterized.ipynb) | BETA | Non | -| 12 | [Projet Createur de Mail personnalise](../../MyIA.AI.Notebooks/GenAI/SemanticKernel/Cr%C3%A9ateur%20de%20mail%20personnalis%C3%A9.ipynb) | BETA | Non | -| 13 | [Notebook de travail — Titanic: exploration, préparation…](../../MyIA.AI.Notebooks/GenAI/SemanticKernel/Notebook-Generated.ipynb) | BETA | Oui | -| 14 | [Notebook de conception de Notebook](../../MyIA.AI.Notebooks/GenAI/SemanticKernel/Semantic-kernel-AutoInteractive.ipynb) | BETA | Non | -| 15 | [Jeu de devinette : Père Fouras vs Laurent Jalabert](../../MyIA.AI.Notebooks/GenAI/SemanticKernel/fort-boyard-python.ipynb) | BETA | Non | +| 12 | [SK-11-A2A : le protocole Agent2Agent à côté de MCP](../../MyIA.AI.Notebooks/GenAI/SemanticKernel/11-SemanticKernel-A2A.ipynb) | BETA | Oui | +| 13 | [Projet Createur de Mail personnalise](../../MyIA.AI.Notebooks/GenAI/SemanticKernel/Cr%C3%A9ateur%20de%20mail%20personnalis%C3%A9.ipynb) | BETA | Non | +| 14 | [Notebook de travail — Titanic: exploration, préparation…](../../MyIA.AI.Notebooks/GenAI/SemanticKernel/Notebook-Generated.ipynb) | BETA | Oui | +| 15 | [Notebook de conception de Notebook](../../MyIA.AI.Notebooks/GenAI/SemanticKernel/Semantic-kernel-AutoInteractive.ipynb) | BETA | Non | +| 16 | [Jeu de devinette : Père Fouras vs Laurent Jalabert](../../MyIA.AI.Notebooks/GenAI/SemanticKernel/fort-boyard-python.ipynb) | BETA | Non | -## GenAI/Texte (33 notebooks) +## GenAI/Texte (39 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| | 1 | [1. Introduction a l'IA generative avec l'API OpenAI](../../MyIA.AI.Notebooks/GenAI/Texte/01_OpenAI_Intro.ipynb) | BETA | Non | | 2 | [2. Prompt Engineering : Techniques Avancées](../../MyIA.AI.Notebooks/GenAI/Texte/02_PromptEngineering.ipynb) | ALPHA | Non | | 3 | [3. Structured Outputs : Sorties JSON Garanties](../../MyIA.AI.Notebooks/GenAI/Texte/03_Structured_Outputs.ipynb) | BETA | Non | -| 4 | [Function Calling : Connecter les LLMs au Monde Réel](../../MyIA.AI.Notebooks/GenAI/Texte/04_Function_Calling.ipynb) | BETA | Non | -| 5 | [5. RAG Modern - Retrieval Augmented Generation](../../MyIA.AI.Notebooks/GenAI/Texte/05_RAG_Modern.ipynb) | BETA | Non | -| 6 | [PDF et Web Search : Sources Documentaires avec OpenAI](../../MyIA.AI.Notebooks/GenAI/Texte/06_PDF_Web_Search.ipynb) | BETA | Non | -| 7 | [Code Interpreter : Exécution de Code avec OpenAI](../../MyIA.AI.Notebooks/GenAI/Texte/07_Code_Interpreter.ipynb) | BETA | Non | -| 8 | [8. Reasoning Models](../../MyIA.AI.Notebooks/GenAI/Texte/08_Reasoning_Models.ipynb) | BETA | Non | -| 9 | [9. Production Patterns](../../MyIA.AI.Notebooks/GenAI/Texte/09_Production_Patterns.ipynb) | BETA | Non | -| 10 | [9b. Prompt Security & Red-Teaming sur notre stack…](../../MyIA.AI.Notebooks/GenAI/Texte/09b_Prompt_Security_RedTeam.ipynb) | BETA | Non | -| 11 | [10. Hébergement Local de Modèles Génératifs](../../MyIA.AI.Notebooks/GenAI/Texte/10_LocalLlama.ipynb) | BETA | Non | -| 12 | [10b. Mécanique d'inférence LLM : construire et mesurer…](../../MyIA.AI.Notebooks/GenAI/Texte/10b_Inference_Mechanics.ipynb) | BETA | Non | -| 13 | [10c. Stratégies pour contextes longs — budget de…](../../MyIA.AI.Notebooks/GenAI/Texte/10c_Long_Context_Strategies.ipynb) | BETA | Non | -| 14 | [10d. TensorSharp : pilote d'inférence LLM native .NET](../../MyIA.AI.Notebooks/GenAI/Texte/10d_TensorSharp_DotNet_Inference.ipynb) | BETA | Non | -| 15 | [10e. LLamaSharp : bake-off binding .NET de llama.cpp](../../MyIA.AI.Notebooks/GenAI/Texte/10e_LLamaSharp_DotNet_BakeOff.ipynb) | BETA | Non | -| 16 | [10f. ONNX Runtime GenAI : jambe finale du bake-off .NET](../../MyIA.AI.Notebooks/GenAI/Texte/10f_ORTGenAI_DotNet_BakeOff.ipynb) | BETA | Non | -| 17 | [11. Quantization](../../MyIA.AI.Notebooks/GenAI/Texte/11_Quantization.ipynb) | BETA | Non | -| 18 | [12. Test Time Scaling](../../MyIA.AI.Notebooks/GenAI/Texte/12_Test_Time_Scaling.ipynb) | BETA | Non | -| 19 | [13. Orchestration agentique du test-time scaling](../../MyIA.AI.Notebooks/GenAI/Texte/13_Agentic_Orchestration.ipynb) | BETA | Non | -| 20 | [13b — Évaluation d'agents : succès, coût, ablation et…](../../MyIA.AI.Notebooks/GenAI/Texte/13b_Agent_Evaluation.ipynb) | BETA | Non | -| 21 | [14. Memoire persistante pour le test-time scaling](../../MyIA.AI.Notebooks/GenAI/Texte/14_Persistent_Memory.ipynb) | BETA | Non | -| 22 | [15. Tree-of-Thoughts sur de vrais problemes de…](../../MyIA.AI.Notebooks/GenAI/Texte/15_Tree_of_Thoughts_Search.ipynb) | BETA | Non | -| 23 | [16. Scaling du test-time compute (Snell 2024)](../../MyIA.AI.Notebooks/GenAI/Texte/16_Scaling_Test_Time_Compute.ipynb) | BETA | Non | -| 24 | [17. Modèles a raisonnement natif vs scaling du…](../../MyIA.AI.Notebooks/GenAI/Texte/17_Native_Reasoning_vs_Scaling.ipynb) | BETA | Non | -| 25 | [18. Plugins Semantic Kernel pour le test-time scaling](../../MyIA.AI.Notebooks/GenAI/Texte/18_Semantic_Kernel_Plugins.ipynb) | BETA | Non | -| 26 | [19. Orchestration et tâches planifiées avec Open WebUI…](../../MyIA.AI.Notebooks/GenAI/Texte/19_OWUI_Orchestration.ipynb) | BETA | Non | -| 27 | [20. OWUI Native API v0.9.6 — introspection REST et…](../../MyIA.AI.Notebooks/GenAI/Texte/20_OWUI_Native_API.ipynb) | BETA | Non | -| 28 | [22 — Évaluer les sorties générées : BLEU, ROUGE,…](../../MyIA.AI.Notebooks/GenAI/Texte/22_Evaluating_Generated_Text.ipynb) | BETA | Non | -| 29 | [22b — Profil cognitif d'un LLM : batterie CHC, profil «…](../../MyIA.AI.Notebooks/GenAI/Texte/22b_Profil_Cognitif_CHC.ipynb) | BETA | Non | -| 30 | [TV-00a — RoPE from scratch : coder la position par…](../../MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-00a-RoPE-from-scratch.ipynb) | BETA | Oui | -| 31 | [TV-00b — Variantes d'attention : MHA, MQA, GQA, SWA](../../MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-00b-Attention-Variants-from-scratch.ipynb) | BETA | Non | -| 32 | [TV-01 — La boîte ouverte côté industrie : Mistral-7B…](../../MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-01-Attention-Variants-SOTA.ipynb) | BETA | Non | -| 33 | [TV-02 — MoE SOTA : le routage réel d'OLMoE-1B-7B](../../MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-02-MoE-SOTA.ipynb) | BETA | Non | +| 4 | [3b. Décisions typées « système 1 » : décider sans…](../../MyIA.AI.Notebooks/GenAI/Texte/03b_Typed_Decisions_System1.ipynb) | BETA | Non | +| 5 | [3c. Décodage contraint au niveau du token](../../MyIA.AI.Notebooks/GenAI/Texte/03c_Constrained_Decoding_Python.ipynb) | BETA | Oui | +| 6 | [Function Calling : Connecter les LLMs au Monde Réel](../../MyIA.AI.Notebooks/GenAI/Texte/04_Function_Calling.ipynb) | BETA | Non | +| 7 | [5. RAG Modern - Retrieval Augmented Generation](../../MyIA.AI.Notebooks/GenAI/Texte/05_RAG_Modern.ipynb) | BETA | Non | +| 8 | [PDF et Web Search : Sources Documentaires avec OpenAI](../../MyIA.AI.Notebooks/GenAI/Texte/06_PDF_Web_Search.ipynb) | BETA | Non | +| 9 | [Code Interpreter : Exécution de Code avec OpenAI](../../MyIA.AI.Notebooks/GenAI/Texte/07_Code_Interpreter.ipynb) | BETA | Non | +| 10 | [8. Reasoning Models](../../MyIA.AI.Notebooks/GenAI/Texte/08_Reasoning_Models.ipynb) | BETA | Non | +| 11 | [9. Production Patterns](../../MyIA.AI.Notebooks/GenAI/Texte/09_Production_Patterns.ipynb) | BETA | Non | +| 12 | [9b. Prompt Security & Red-Teaming sur notre stack…](../../MyIA.AI.Notebooks/GenAI/Texte/09b_Prompt_Security_RedTeam.ipynb) | BETA | Non | +| 13 | [9c. Routage et Repli : choisir le bon modèle, au bon…](../../MyIA.AI.Notebooks/GenAI/Texte/09c_Production_Routage_Repli.ipynb) | BETA | Non | +| 14 | [9d. Production Caches : payer une fois, servir mille…](../../MyIA.AI.Notebooks/GenAI/Texte/09d_Production_Caches.ipynb) | BETA | Non | +| 15 | [10. Hébergement Local de Modèles Génératifs](../../MyIA.AI.Notebooks/GenAI/Texte/10_LocalLlama.ipynb) | BETA | Non | +| 16 | [10b. Mécanique d'inférence LLM : construire et mesurer…](../../MyIA.AI.Notebooks/GenAI/Texte/10b_Inference_Mechanics.ipynb) | BETA | Non | +| 17 | [10c. Stratégies pour contextes longs — budget de…](../../MyIA.AI.Notebooks/GenAI/Texte/10c_Long_Context_Strategies.ipynb) | BETA | Non | +| 18 | [10d. TensorSharp : pilote d'inférence LLM native .NET](../../MyIA.AI.Notebooks/GenAI/Texte/10d_TensorSharp_DotNet_Inference.ipynb) | BETA | Non | +| 19 | [10e. LLamaSharp : bake-off binding .NET de llama.cpp](../../MyIA.AI.Notebooks/GenAI/Texte/10e_LLamaSharp_DotNet_BakeOff.ipynb) | BETA | Non | +| 20 | [10f. ONNX Runtime GenAI : jambe finale du bake-off .NET](../../MyIA.AI.Notebooks/GenAI/Texte/10f_ORTGenAI_DotNet_BakeOff.ipynb) | BETA | Non | +| 21 | [11. Quantization](../../MyIA.AI.Notebooks/GenAI/Texte/11_Quantization.ipynb) | BETA | Non | +| 22 | [12. Test Time Scaling](../../MyIA.AI.Notebooks/GenAI/Texte/12_Test_Time_Scaling.ipynb) | BETA | Non | +| 23 | [13. Orchestration agentique du test-time scaling](../../MyIA.AI.Notebooks/GenAI/Texte/13_Agentic_Orchestration.ipynb) | BETA | Non | +| 24 | [13b — Évaluation d'agents : succès, coût, ablation et…](../../MyIA.AI.Notebooks/GenAI/Texte/13b_Agent_Evaluation.ipynb) | BETA | Non | +| 25 | [14. Memoire persistante pour le test-time scaling](../../MyIA.AI.Notebooks/GenAI/Texte/14_Persistent_Memory.ipynb) | BETA | Non | +| 26 | [14b. Memoire paginee d'agent -- fenetre glissante,…](../../MyIA.AI.Notebooks/GenAI/Texte/14b_Paginated_Memory-Python.ipynb) | BETA | Oui | +| 27 | [15. Tree-of-Thoughts sur de vrais problemes de…](../../MyIA.AI.Notebooks/GenAI/Texte/15_Tree_of_Thoughts_Search.ipynb) | BETA | Non | +| 28 | [16. Scaling du test-time compute (Snell 2024)](../../MyIA.AI.Notebooks/GenAI/Texte/16_Scaling_Test_Time_Compute.ipynb) | BETA | Non | +| 29 | [17. Modèles a raisonnement natif vs scaling du…](../../MyIA.AI.Notebooks/GenAI/Texte/17_Native_Reasoning_vs_Scaling.ipynb) | BETA | Non | +| 30 | [18. Plugins Semantic Kernel pour le test-time scaling](../../MyIA.AI.Notebooks/GenAI/Texte/18_Semantic_Kernel_Plugins.ipynb) | BETA | Non | +| 31 | [19. Orchestration et tâches planifiées avec Open WebUI…](../../MyIA.AI.Notebooks/GenAI/Texte/19_OWUI_Orchestration.ipynb) | BETA | Non | +| 32 | [20. OWUI Native API v0.9.6 — introspection REST et…](../../MyIA.AI.Notebooks/GenAI/Texte/20_OWUI_Native_API.ipynb) | BETA | Non | +| 33 | [22 — Évaluer les sorties générées : BLEU, ROUGE,…](../../MyIA.AI.Notebooks/GenAI/Texte/22_Evaluating_Generated_Text.ipynb) | BETA | Non | +| 34 | [22b — Profil cognitif d'un LLM : batterie CHC, profil «…](../../MyIA.AI.Notebooks/GenAI/Texte/22b_Profil_Cognitif_CHC.ipynb) | BETA | Non | +| 35 | [TV-00a — RoPE from scratch : coder la position par…](../../MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-00a-RoPE-from-scratch.ipynb) | BETA | Oui | +| 36 | [TV-00b — Variantes d'attention : MHA, MQA, GQA, SWA](../../MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-00b-Attention-Variants-from-scratch.ipynb) | BETA | Non | +| 37 | [TV-01 — La boîte ouverte côté industrie : Mistral-7B…](../../MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-01-Attention-Variants-SOTA.ipynb) | BETA | Non | +| 38 | [TV-02 — MoE SOTA : le routage réel d'OLMoE-1B-7B](../../MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-02-MoE-SOTA.ipynb) | BETA | Non | +| 39 | [TV-03 -- Internalisation du raisonnement (CoT -> calcul…](../../MyIA.AI.Notebooks/GenAI/Texte/TransformerVariants/TV-03-Internalisation-CoT.ipynb) | BETA | Oui | ## GenAI/Vibe-Coding (8 notebooks) @@ -306,7 +315,7 @@ Génération d'images (DALL-E, Stable Diffusion, Qwen, ComfyUI), synthèse vocal | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| -| 1 | [Opérations de Base sur les Videos](../../MyIA.AI.Notebooks/GenAI/Video/01-Foundation/01-1-Video-Operations-Basics.ipynb) | BETA | Non | +| 1 | [Opérations de Base sur les Videos](../../MyIA.AI.Notebooks/GenAI/Video/01-Foundation/01-1-Video-Operations-Basics.ipynb) | ALPHA | Non | | 2 | [Bonus Slideshow Vidéo - Générateur de Slideshow…](../../MyIA.AI.Notebooks/GenAI/Video/01-Foundation/01-1b-Video-Slideshow-Bonus.ipynb) | ALPHA | Oui | | 3 | [GPT-5 Video Understanding - Comprehension Video par IA](../../MyIA.AI.Notebooks/GenAI/Video/01-Foundation/01-2-GPT-5-Video-Understanding.ipynb) | BETA | Non | | 4 | [Qwen2.5-VL Video Analysis - Comprehension Video Locale](../../MyIA.AI.Notebooks/GenAI/Video/01-Foundation/01-3-Qwen-VL-Video-Analysis.ipynb) | BETA | Non | diff --git a/docs/curriculum/ia-symbolique.md b/docs/curriculum/ia-symbolique.md index d1e9b1dc52..2bf76b03c5 100644 --- a/docs/curriculum/ia-symbolique.md +++ b/docs/curriculum/ia-symbolique.md @@ -20,10 +20,10 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | Métrique | Valeur | |----------|--------| -| Notebooks | 303 | +| Notebooks | 308 | | PRODUCTION | 0 | -| BETA | 296 | -| ALPHA | 7 | +| BETA | 299 | +| ALPHA | 9 | ## SymbolicAI (1 notebooks) @@ -31,128 +31,126 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, |---|----------|----------|------------| | 1 | [Configuration de l'environnement C#](../../MyIA.AI.Notebooks/SymbolicAI/OR-tools-Stiegler.ipynb) | BETA | Oui | -## SymbolicAI/Argument_Analysis (35 notebooks) +## SymbolicAI/Argument_Analysis (31 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| -| 1 | [Configuration de l'environnement (JVM Tweety réelle,…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-00-Setup-Tweety-Python.ipynb) | BETA | Oui | -| 2 | [Analyse rhétorique collaborative par agents IA…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/_archive/Argument_Analysis_Agentic-0-init_agent.ipynb) | BETA | Non | -| 3 | [Détection de sophismes par taxonomie](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-02-Fallacies-Detection-Python.ipynb) | BETA | Oui | -| 4 | [Agent InformalAnalysisAgent (définitions)](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/_archive/Argument_Analysis_Agentic-1-informal_agent.ipynb) | BETA | Non | -| 5 | [Vérification logique formelle avec Tweety](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-05-Formal-Verification-Python.ipynb) | BETA | Oui | -| 6 | [Agent PropositionalLogicAgent (définitions)](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/_archive/Argument_Analysis_Agentic-2-pl_agent.ipynb) | BETA | Oui | -| 7 | [Deux paradigmes d'orchestration](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-07-Orchestration-Python.ipynb) | BETA | Oui | -| 8 | [Orchestration de la conversation multi-agents](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/_archive/Argument_Analysis_Agentic-3-orchestration_agent.ipynb) | BETA | Non | -| 9 | [Capstone d'intégration (baseline 0-shot vs pipeline)](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08-Capstone-Python.ipynb) | BETA | Oui | -| 10 | [Truth Maintenance System (JTMS) déterministe](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-06-JTMS-Python.ipynb) | BETA | Oui | -| 11 | [ArgumentProfile : la fiche d'identité…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08e-Argument-Profile-Python.ipynb) | BETA | Oui | -| 12 | [Argumentum : la carte de sophisme, du nœud de taxonomie…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-02b-Argumentum-Cards-Python.ipynb) | BETA | Oui | -| 13 | [Le bus de communication multi-agents — le contrat,…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-07b-Communication-Channels-Python.ipynb) | BETA | Oui | -| 14 | [Graphes d'argumentation datés — l'instrument $G_t^{arg}…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Obs-01-Graphes-Dates-Python.ipynb) | BETA | Oui | -| 15 | [Dialogues protocolisés : inquiry et persuasion…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-04-Dialogues-Protocolises-Python.ipynb) | BETA | Oui | -| 16 | [Argumentation abstraite de Dung — sémantiques grounded,…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-03-Dung-AF-Semantics-Python.ipynb) | BETA | Oui | -| 17 | [Analyse rhétorique collaborative par agents IA —…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08b-Executor-Python.ipynb) | BETA | Non | -| 18 | [La base de connaissances d'un débat — propositions,…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-04b-Knowledge-Base-Python.ipynb) | BETA | Oui | -| 19 | [Routage multi-backend : décider ou échouer bruyamment](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-05b-Multi-Backend-Routing-Python.ipynb) | BETA | Oui | -| 20 | [Observatoire des formes relationnelles — Cas 1](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Obs-02-Initiation-Python.ipynb) | BETA | Oui | -| 21 | [Ontologie AIF.owl — l'architecture Argumentum des…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Onto-01-AIF-OWL2-Python.ipynb) | ALPHA | Oui | -| 22 | [Liens croisés crossLink et attaques AIF du CSV…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Onto-02-CrossLinks-CSV-Python.ipynb) | BETA | Oui | -| 23 | [Ontologie des vertus argumentatives — le pôle miroir…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Onto-03-Vertus-SKOS-Python.ipynb) | BETA | Oui | -| 24 | [Argumentation graduée — sémantiques de classement…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-03c-Ranking-Semantics-Python.ipynb) | BETA | Oui | -| 25 | [Strate 6 : le banc de recollement](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Obs-03-Recollement-Lectures-Python.ipynb) | BETA | Oui | -| 26 | [Strate 6 : le recollement sur lectures réellement…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Obs-04-Recollement-Strate6-Python.ipynb) | BETA | Oui | -| 27 | [Restitution en 3 actes — scaffold déterministe,…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08d-Restitution-3-Actes-Python.ipynb) | BETA | Non | -| 28 | [Reconnaître un schéma d'argumentation — la table de…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-01b-Schemes-Walton-Python.ipynb) | BETA | Oui | -| 29 | [Le modèle de Toulmin (1958)](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-01-Toulmin-Model-Python.ipynb) | BETA | Oui | -| 30 | [Interface de configuration et préparation du texte](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08c-UI-Configuration-Python.ipynb) | BETA | Oui | -| 31 | [Argumentation basée sur les valeurs (VAF, Bench-Capon…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-03b-Value-Based-AF-Python.ipynb) | BETA | Oui | -| 32 | [I2 — Génération de contre-arguments par raisonnement…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/groupe-I2-contre-arguments-aspic/I2_Contre_arguments_ASPIC.ipynb) | BETA | Oui | -| 33 |[Détection symbolique de sophismes — l'étage symbolique…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Fallacy_Rules_Symboliques.ipynb) | BETA | Oui | -| 34 |[Gouvernance multi-agents : scrutins, protocoles, choix…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Gouvernance_Multi_Agents.ipynb) | BETA | Oui | -| 35 |[Orchestration d'un debat : arbitrer entre sept…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-07c-Orchestration-Modes-Python.ipynb) | BETA | Oui | +| 1 | [Détection symbolique de sophismes — l'étage symbolique…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Fallacy_Rules_Symboliques.ipynb) | BETA | Oui | +| 2 | [Gouvernance multi-agents : scrutins, protocoles, choix…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Gouvernance_Multi_Agents.ipynb) | BETA | Oui | +| 3 | [Configuration de l'environnement (JVM Tweety réelle,…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-00-Setup-Tweety-Python.ipynb) | BETA | Oui | +| 4 | [Le modèle de Toulmin (1958)](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-01-Toulmin-Model-Python.ipynb) | BETA | Oui | +| 5 | [Reconnaître un schéma d'argumentation — la table de…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-01b-Schemes-Walton-Python.ipynb) | BETA | Oui | +| 6 | [Détection de sophismes par taxonomie](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-02-Fallacies-Detection-Python.ipynb) | BETA | Oui | +| 7 | [Argumentum : la carte de sophisme, du nœud de taxonomie…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-02b-Argumentum-Cards-Python.ipynb) | BETA | Oui | +| 8 | [Argumentation abstraite de Dung — sémantiques grounded,…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-03-Dung-AF-Semantics-Python.ipynb) | BETA | Oui | +| 9 | [Argumentation basée sur les valeurs (VAF, Bench-Capon…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-03b-Value-Based-AF-Python.ipynb) | BETA | Oui | +| 10 | [Argumentation graduée — sémantiques de classement…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-03c-Ranking-Semantics-Python.ipynb) | BETA | Oui | +| 11 | [Dialogues protocolisés : inquiry et persuasion…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-04-Dialogues-Protocolises-Python.ipynb) | BETA | Oui | +| 12 | [La base de connaissances d'un débat — propositions,…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-04b-Knowledge-Base-Python.ipynb) | BETA | Oui | +| 13 | [Vérification logique formelle avec Tweety](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-05-Formal-Verification-Python.ipynb) | BETA | Non | +| 14 | [Routage multi-backend : décider ou échouer bruyamment](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-05b-Multi-Backend-Routing-Python.ipynb) | BETA | Oui | +| 15 | [Truth Maintenance System (JTMS) déterministe](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-06-JTMS-Python.ipynb) | BETA | Oui | +| 16 | [Deux paradigmes d'orchestration](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-07-Orchestration-Python.ipynb) | BETA | Oui | +| 17 | [Le bus de communication multi-agents — le contrat,…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-07b-Communication-Channels-Python.ipynb) | BETA | Oui | +| 18 | [Orchestration d'un debat : arbitrer entre sept…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-07c-Orchestration-Modes-Python.ipynb) | BETA | Oui | +| 19 | [Capstone d'intégration (baseline 0-shot vs pipeline)](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08-Capstone-Python.ipynb) | BETA | Oui | +| 20 | [Analyse rhétorique collaborative par agents IA —…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08b-Executor-Python.ipynb) | BETA | Non | +| 21 | [Interface de configuration et préparation du texte](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08c-UI-Configuration-Python.ipynb) | BETA | Oui | +| 22 | [Restitution en 3 actes — scaffold déterministe,…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08d-Restitution-3-Actes-Python.ipynb) | BETA | Non | +| 23 | [ArgumentProfile : la fiche d'identité…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-08e-Argument-Profile-Python.ipynb) | BETA | Oui | +| 24 | [Graphes d'argumentation datés — l'instrument $G_t^{arg}…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Obs-01-Graphes-Dates-Python.ipynb) | BETA | Oui | +| 25 | [Observatoire des formes relationnelles — Cas 1](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Obs-02-Initiation-Python.ipynb) | BETA | Oui | +| 26 | [Strate 6 : le banc de recollement](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Obs-03-Recollement-Lectures-Python.ipynb) | BETA | Oui | +| 27 | [Strate 6 : le recollement sur lectures réellement…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Obs-04-Recollement-Strate6-Python.ipynb) | BETA | Oui | +| 28 | [Ontologie AIF.owl — l'architecture Argumentum des…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Onto-01-AIF-OWL2-Python.ipynb) | ALPHA | Oui | +| 29 | [Liens croisés crossLink et attaques AIF du CSV…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Onto-02-CrossLinks-CSV-Python.ipynb) | BETA | Oui | +| 30 | [Ontologie des vertus argumentatives — le pôle miroir…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argumentation-Onto-03-Vertus-SKOS-Python.ipynb) | BETA | Oui | +| 31 | [I2 — Génération de contre-arguments par raisonnement…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/groupe-I2-contre-arguments-aspic/I2_Contre_arguments_ASPIC.ipynb) | BETA | Oui | -## SymbolicAI/Lean/Geometry (4 notebooks) +## SymbolicAI/Lean (80 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| -| 1 | [Geometry 01 — De la figure à l'équation](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-01-From-Figure-To-Equation.ipynb) | BETA | Oui | -| 2 | [Geometry 02 — Prouver par l'algèbre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-02-From-Equation-To-Proof.ipynb) | BETA | Oui | -| 3 | [Geometry 03 — La méthode de Wu](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-03-Wu-Method-Python.ipynb) | BETA | Oui | -| 4 | [Geometry 03b — Décomposition de Ritt et composantes…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-03b-Ritt-Decomposition-Python.ipynb) | BETA | Oui | - -## SymbolicAI/Lean (69 notebooks) - -| # | Notebook | Maturité | Exécutable | -|---|----------|----------|------------| -| 1 | [Langlands 01 : formes modulaires — de SL₂(ℤ) aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Langlands/01-formes-modulaires-sl2z-hecke.ipynb) | BETA | Non | -| 2 | [Lean 4 - Installation et Configuration](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-01-Setup-Lean-Python.ipynb) | BETA | Non | -| 3 | [Lean 10 : LeanDojo - ML/LLM Theorem Proving](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-10-LeanDojo.ipynb) | BETA | Non | -| 4 | [Lean 11 - TorchLean : Réseaux de Neurones Formellement…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-11-TorchLean.ipynb) | BETA | Non | -| 5 | [Lean 11b - TorchLean : Implémentation Python des…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-11b-TorchLean-Python.ipynb) | BETA | Non | -| 6 | [Lean-12 : Le Théorème de Sensibilité (Huang 2019)](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12-Sensitivity-Theorem.ipynb) | BETA | Non | -| 7 | [Lean-12b — Théorème de Sensibilité de Huang (companion…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12b-Lean-Sensitivity-Theorem.ipynb) | BETA | Non | -| 8 | [Lean-13 : Le Théorème de Kochen-Specker (Cabello 18…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13-Kochen-Specker.ipynb) | BETA | Non | -| 9 | [Lean-13b : la borne de Tsirelson — digestion formelle…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13b-CHSH-Tsirelson-Native.ipynb) | BETA | Non | -| 10 | [Lean-13c : la saturation de Tsirelson — le témoin de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13c-CHSH-Landau-Saturation.ipynb) | BETA | Non | -| 11 | [Lean-15 : Hommage a Alexandre Grothendieck -- Le…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15-Grothendieck-Tribute.ipynb) | BETA | Non | -| 12 | [Lean-15b : Grothendieck en Lean -- Atelier pratique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15b-Lean-Grothendieck.ipynb) | BETA | Non | -| 13 | [Lean-15c : le lake Grothendieck par ses énoncés…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15c-Lean-Grothendieck-Companion.ipynb) | BETA | Non | -| 14 | [Lean-16a - Conway, l'homme et l'oeuvre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16a-Conway-Man-and-Work.ipynb) | BETA | Non | -| 15 | [Lean-16b : Hommage a John Conway — Game of Life as…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16b-Conway-Game-of-Life-Lean.ipynb) | BETA | Non | -| 16 | [Lean-16c - Conway Game of Life : les 3 piliers, en…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16c-Conway-Game-of-Life-Golly.ipynb) | BETA | Non | -| 17 | [Lean-16d : Game of Life sur kernel Lean natif](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16d-Conway-Game-of-Life-Lean-Native.ipynb) | BETA | Non | -| 18 | [Lean-16e : FRACTRAN, la machine universelle de Conway,…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16e-Conway-FRACTRAN-Lean-Native.ipynb) | BETA | Non | -| 19 | [Lean-16f : Le Théorème du Libre Arbitre (Conway-Kochen)](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16f-Conway-Free-Will-Theorem.ipynb) | BETA | Non | -| 20 | [Lean 16g — Canons : le barreau 2 de l'échelle des…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16g-Conway-Canons.ipynb) | BETA | Non | -| 21 | [Lean-16h : la tournée des motifs du Jeu de la Vie —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16h-Conway-PatternTour-Native.ipynb) | BETA | Non | -| 22 | [Lean-16i — Synthèse d'un translateur minuscule :…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16i-Translateur-Life.ipynb) | BETA | Non | -| 23 | [Lean-16j : la preuve de correction Hashlife — compagnon…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16j-Conway-Hashlife-Correctness-Native.ipynb) | BETA | Non | -| 24 | [Lean 17a — Conway, les Nœuds et la Preuve de Piccirillo](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17a-Knots-Conway-Proofs.ipynb) | BETA | Non | -| 25 | [Lean 17b — Invariants de Nœuds : Calcul et Vérification](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17b-Knots-Invariants-Companion.ipynb) | BETA | Non | -| 26 | [Lean 17c — Le lake knot_lean par ses déclarations…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17c-Knots-Companion-Formel.ipynb) | BETA | Non | -| 27 | [ANALYSE-01 — La Conjecture de Sendov (preuve L. Mazur,…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-01-Sendov-Lean-Python.ipynb) | BETA | Non | -| 28 | [ANALYSE-02 — Le manuel *Analysis I* de T. Tao en Lean 4…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-02-Tao-Lean-Python.ipynb) | BETA | Non | -| 29 | [Lean 2 - Types Dependants et Calcul des Constructions](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-02-Dependent-Types-Lean.ipynb) | BETA | Non | -| 30 | [ANALYSE-03 — La conjecture de Freiman-Ruzsa polynomiale…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-03-PFR-Lean.ipynb) | BETA | Non | -| 31 | [ANALYSE-04 — Trois primitives de PFR, et l'endroit exact…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-04-PFR-Primitives-Python.ipynb) | BETA | Non | -| 32 | [Lean-21 : Detection MIMO par flips -- le seuil 2 log N…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21-MIMO-Detection-Flips.ipynb) | BETA | Non | -| 33 | [Lean-21b : le lake mimo_lean par ses énoncés —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21b-MIMO-Converse-Native.ipynb) | BETA | Non | -| 34 | [Lean-21c : Le budget de descente - quand la…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21c-Descente-Budget.ipynb) | BETA | Non | -| 35 | [Lean-22 : Le problème inverse de Galois — M₂₃ refermé…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-22-Galois-Probleme-Inverse-M23.ipynb) | BETA | Non | -| 36 | [Lean-23 : ERC-20 sous Lean 4 — l'invariant de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-23-ERC20-Invariant-Companion.ipynb) | BETA | Non | -| 37 | [Lean-23b — ERC-20 natif : l'invariant de conservation…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-23b-Lean-ERC20-Native-Companion.ipynb) | BETA | Non | -| 38 | [Lean-24 : le lake calibration_lean par ses énoncés —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-24-Calibration-Native-Companion.ipynb) | BETA | Non | -| 39 | [Lean-24b : Confiance et preuves — quand un certificat…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-24b-Confiance-Preuves-Native.ipynb) | BETA | Non | -| 40 | [Lean-25 — Cohérence et témoin : de Finetti construit le…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-25-Coherence-et-Temoin.ipynb) | BETA | Non | -| 41 | [Lean-26 : Hommage à James R. Munkres — le cours 18.901…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-26-Munkres-Tribute.ipynb) | BETA | Non | -| 42 | [Lean-27 : coloration d'arêtes et conjecture de Tutte —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-27-EdgeColoring-Tutte-Companion.ipynb) | BETA | Non | -| 43 | [Lean-28 : Le problème de Hopf sur S⁶ — digestion d'une…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-28-Complex-Structure-S6.ipynb) | BETA | Non | -| 44 | [Lean-29 : les opérateurs de Hecke $T_p$ et $U_p$ —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-29-Hecke-Operators-Native.ipynb) | BETA | Non | -| 45 | [Lean 3 - Propositions et Preuves](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-03-Propositions-Proofs-Lean.ipynb) | BETA | Non | -| 46 | [Lean-30 : groupes formels multivariés — compagnon natif](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-30-FormalGroups-Native.ipynb) | BETA | Non | -| 47 | [Lean-31 : Euler et Navier–Stokes — reproduction pinée,…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-31-Euler-Navier-Stokes.ipynb) | BETA | Non | -| 48 | [Lean-33 : espaces de Schwartz — décroissance et…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-33-Distribution-Spaces.ipynb) | BETA | Non | -| 49 | [Lean-34 — Calculabilité et limites : de l'arrêt aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-34-Calculabilite-et-Limites.ipynb) | BETA | Non | -| 50 | [Lean-34b — FairBot par le théorème de Löb : coopérer…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-34b-FairBot-Loeb.ipynb) | BETA | Non | -| 51 | [Lean-36 : structures mathematiques finies — l'Annexe A…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-36-Structures-Finies-MUH-Lean.ipynb) | BETA | Non | -| 52 | [Lean-37 : Capstone — la sous-série « Serre 100 »](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-37-Capstone-Serre100.ipynb) | BETA | Non | -| 53 | [Lean-3b — Formalized Formal Logic : le laboratoire…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-03b-Formalized-Formal-Logic-Lean-Python.ipynb) | BETA | Non | -| 54 | [Lean 4 - Quantificateurs et Logique du Premier Ordre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-04-Quantifiers-Lean.ipynb) | BETA | Non | -| 55 | [Lean 5 - Mode Tactique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-05-Tactics-Lean.ipynb) | BETA | Non | -| 56 | [Lean 6 - Mathlib4 : La Bibliotheque Mathematique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-06-Mathlib-Essentials-Lean.ipynb) | BETA | Non | -| 57 | [Lean 7 - Integration des LLMs pour l'Assistance aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-07-LLM-Integration-Lean-Python.ipynb) | BETA | Non | -| 58 | [Lean 7b - Exemples Progressifs et Benchmarks](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-07b-Examples-Python.ipynb) | BETA | Non | -| 59 | [Lean-8 - Agents Autonomes pour Demonstration de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-08-Agentic-Proving-Python.ipynb) | BETA | Non | -| 60 | [Lean 8b : le programme Erdős et le pattern…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-08b-Erdos-Formal-Conjectures-Lean.ipynb) | BETA | Non | -| 61 | [Lean 9 : Multi-Agents avec Semantic Kernel](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-09-SK-Multi-Agents-Lean-Python.ipynb) | BETA | Non | -| 62 | [Corps finis et la borne de Hasse — distiller un…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/01-corps-finis-borne-hasse.ipynb) | BETA | Non | -| 63 | [2. Valeurs zêta multiples finies — l'anneau des adèles…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/02-valeurs-zeta-multiples-finies.ipynb) | BETA | Non | -| 64 | [Cohomologie de Čech calculée — espaces topologiques…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/03-cohomologie-cech-espaces-finis.ipynb) | BETA | Non | -| 65 | [Lemme de Yoneda calculé — catégories finies](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/04-lemme-yoneda-categories-finies.ipynb) | BETA | Non | -| 66 | [5. Tables de caractères — le squelette combinatoire…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/05-table-de-caracteres.ipynb) | BETA | Non | -| 67 | [Les bulles diaboliques de Minkowski — géométrie des…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/06-bulles-minkowski.ipynb) | BETA | Non | -| 68 | [Zéros de fonctions L, gaps et statistique GUE](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/07-zeros-fonctions-l-gaps-gue.ipynb) | BETA | Non | -| 69 | [Serre dans Mathlib — tour guidé des cinq monuments](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/08-serre-dans-mathlib.ipynb) | BETA | Non | +| 1 | [ANALYSE-01 : La Conjecture de Sendov (preuve L. Mazur,…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-01-Sendov-Lean-Python.ipynb) | BETA | Non | +| 2 | [ANALYSE-02 : Le manuel *Analysis I* de T. Tao en Lean 4…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-02-Tao-Lean-Python.ipynb) | BETA | Non | +| 3 | [ANALYSE-03 : La conjecture de Freiman-Ruzsa polynomiale…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-03-PFR-Lean.ipynb) | BETA | Non | +| 4 | [ANALYSE-04 : Trois primitives de PFR, et l'endroit…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-04-PFR-Primitives-Python.ipynb) | BETA | Non | +| 5 | [Geometry 01 — De la figure à l'équation](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-01-From-Figure-To-Equation.ipynb) | BETA | Non | +| 6 | [Geometry 02 — Prouver par l'algèbre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-02-From-Equation-To-Proof.ipynb) | BETA | Non | +| 7 | [Geometry 03 — La méthode de Wu](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-03-Wu-Method-Python.ipynb) | BETA | Non | +| 8 | [Geometry 03b — Décomposition de Ritt et composantes…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-03b-Ritt-Decomposition-Python.ipynb) | BETA | Non | +| 9 | [Geometry 04 — Raisonner comme un géomètre (DD + AR)](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-04-DD-AR-Python.ipynb) | BETA | Non | +| 10 | [Langlands 01 : formes modulaires — de SL₂(ℤ) aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Langlands/01-formes-modulaires-sl2z-hecke.ipynb) | BETA | Non | +| 11 | [Monstrous Moonshine : l'invariant $j$ et le monstre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Langlands/02-monstrous-moonshine-invariant-j.ipynb) | BETA | Non | +| 12 | [Lean 4 - Installation et Configuration](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-01-Setup-Lean-Python.ipynb) | BETA | Non | +| 13 | [Lean 2 - Types Dependants et Calcul des Constructions](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-02-Dependent-Types-Lean.ipynb) | BETA | Non | +| 14 | [Lean 3 - Propositions et Preuves](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-03-Propositions-Proofs-Lean.ipynb) | BETA | Non | +| 15 | [Lean-3b — Formalized Formal Logic : le laboratoire…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-03b-Formalized-Formal-Logic-Lean-Python.ipynb) | BETA | Non | +| 16 | [Lean 4 - Quantificateurs et Logique du Premier Ordre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-04-Quantifiers-Lean.ipynb) | BETA | Non | +| 17 | [Lean 5 - Mode Tactique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-05-Tactics-Lean.ipynb) | BETA | Non | +| 18 | [Lean 6 - Mathlib4 : La Bibliotheque Mathematique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-06-Mathlib-Essentials-Lean.ipynb) | BETA | Non | +| 19 | [Lean 7 - Integration des LLMs pour l'Assistance aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-07-LLM-Integration-Lean-Python.ipynb) | BETA | Non | +| 20 | [Lean 7b - Exemples Progressifs et Benchmarks](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-07b-Examples-Python.ipynb) | BETA | Non | +| 21 | [Lean-8 - Agents Autonomes pour Demonstration de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-08-Agentic-Proving-Python.ipynb) | BETA | Non | +| 22 | [Lean 8b : le programme Erdős et le pattern…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-08b-Erdos-Formal-Conjectures-Lean.ipynb) | BETA | Non | +| 23 | [Lean 9 : Multi-Agents avec Semantic Kernel](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-09-SK-Multi-Agents-Lean-Python.ipynb) | BETA | Non | +| 24 | [Lean 10 : LeanDojo - ML/LLM Theorem Proving](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-10-LeanDojo.ipynb) | BETA | Non | +| 25 | [Lean 11 - TorchLean : Réseaux de Neurones Formellement…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-11-TorchLean.ipynb) | BETA | Non | +| 26 | [Lean 11b - TorchLean : Implémentation Python des…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-11b-TorchLean-Python.ipynb) | BETA | Non | +| 27 | [Lean-12 : Le Théorème de Sensibilité (Huang 2019)](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12-Sensitivity-Theorem.ipynb) | BETA | Non | +| 28 | [Lean-12b — Théorème de Sensibilité de Huang (companion…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12b-Lean-Sensitivity-Theorem.ipynb) | BETA | Non | +| 29 | [Lean-12c : algèbre TPR — binding, unbinding et…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12c-Tensor-Product-Representations-Lean.ipynb) | BETA | Non | +| 30 | [Lean-13 : Le Théorème de Kochen-Specker (Cabello 18…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13-Kochen-Specker.ipynb) | BETA | Non | +| 31 | [Lean-13b : la borne de Tsirelson — digestion formelle…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13b-CHSH-Tsirelson-Native.ipynb) | BETA | Non | +| 32 | [Lean-13c : la saturation de Tsirelson — le témoin de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13c-CHSH-Landau-Saturation.ipynb) | BETA | Non | +| 33 | [Lean-15 : Hommage a Alexandre Grothendieck -- Le…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15-Grothendieck-Tribute.ipynb) | BETA | Non | +| 34 | [Lean-15b : Grothendieck en Lean -- Atelier pratique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15b-Lean-Grothendieck.ipynb) | BETA | Non | +| 35 | [Lean-15c : le lake Grothendieck par ses énoncés…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15c-Lean-Grothendieck-Companion.ipynb) | BETA | Non | +| 36 | [Lean-15d : Grothendieck en images](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15d-Lean-Grothendieck-Visuel-Python.ipynb) | ALPHA | Non | +| 37 | [Lean-16a - Conway, l'homme et l'oeuvre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16a-Conway-Man-and-Work.ipynb) | BETA | Non | +| 38 | [Lean-16b : Hommage a John Conway — Game of Life as…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16b-Conway-Game-of-Life-Lean.ipynb) | BETA | Non | +| 39 | [Lean-16c - Conway Game of Life : les 3 piliers, en…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16c-Conway-Game-of-Life-Golly.ipynb) | BETA | Non | +| 40 | [Lean-16d : Game of Life sur kernel Lean natif](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16d-Conway-Game-of-Life-Lean-Native.ipynb) | BETA | Non | +| 41 | [Lean-16e : FRACTRAN, la machine universelle de Conway,…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16e-Conway-FRACTRAN-Lean-Native.ipynb) | BETA | Non | +| 42 | [Lean-16f : Le Théorème du Libre Arbitre (Conway-Kochen)](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16f-Conway-Free-Will-Theorem.ipynb) | BETA | Non | +| 43 | [Lean 16g — Canons : le barreau 2 de l'échelle des…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16g-Conway-Canons.ipynb) | BETA | Non | +| 44 | [Lean-16h : la tournée des motifs du Jeu de la Vie —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16h-Conway-PatternTour-Native.ipynb) | BETA | Non | +| 45 | [Lean-16i — Synthèse d'un translateur minuscule :…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16i-Translateur-Life.ipynb) | BETA | Non | +| 46 | [Lean-16j : la preuve de correction Hashlife — compagnon…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16j-Conway-Hashlife-Correctness-Native.ipynb) | BETA | Non | +| 47 | [Lean 17a — Conway, les Nœuds et la Preuve de Piccirillo](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17a-Knots-Conway-Proofs.ipynb) | BETA | Non | +| 48 | [Lean 17b — Invariants de Nœuds : Calcul et Vérification](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17b-Knots-Invariants-Companion.ipynb) | BETA | Non | +| 49 | [Lean 17c — Le lake knot_lean par ses déclarations…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17c-Knots-Companion-Formel.ipynb) | BETA | Non | +| 50 | [Lean-20 : Capstone — digérer le travail formel de Tao…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-20-Capstone-Digestions-Tao-Python.ipynb) | BETA | Non | +| 51 | [Lean-21 : Detection MIMO par flips -- le seuil 2 log N…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21-MIMO-Detection-Flips.ipynb) | BETA | Non | +| 52 | [Lean-21b : le lake mimo_lean par ses énoncés —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21b-MIMO-Converse-Native.ipynb) | BETA | Non | +| 53 | [Lean-21c : Le budget de descente - quand la…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21c-Descente-Budget.ipynb) | BETA | Non | +| 54 | [Lean-22 : Le problème inverse de Galois — M₂₃ refermé…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-22-Galois-Probleme-Inverse-M23.ipynb) | BETA | Non | +| 55 | [Lean-23 : ERC-20 sous Lean 4 — l'invariant de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-23-ERC20-Invariant-Companion.ipynb) | BETA | Non | +| 56 | [Lean-23b — ERC-20 natif : l'invariant de conservation…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-23b-Lean-ERC20-Native-Companion.ipynb) | BETA | Non | +| 57 | [Lean-24 : le lake calibration_lean par ses énoncés —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-24-Calibration-Native-Companion.ipynb) | BETA | Non | +| 58 | [Lean-24b : Confiance et preuves — quand un certificat…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-24b-Confiance-Preuves-Native.ipynb) | BETA | Non | +| 59 | [Lean-25 — Cohérence et témoin : de Finetti construit le…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-25-Coherence-et-Temoin.ipynb) | BETA | Non | +| 60 | [Lean-26 : Hommage à James R. Munkres — le cours 18.901…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-26-Munkres-Tribute.ipynb) | BETA | Non | +| 61 | [Lean-27 : coloration d'arêtes et conjecture de Tutte —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-27-EdgeColoring-Tutte-Companion.ipynb) | BETA | Non | +| 62 | [Lean-28 : Le problème de Hopf sur S⁶ — digestion d'une…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-28-Complex-Structure-S6.ipynb) | BETA | Non | +| 63 | [Lean-29 : les opérateurs de Hecke $T_p$ et $U_p$ —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-29-Hecke-Operators-Native.ipynb) | BETA | Non | +| 64 | [Lean-30 : groupes formels multivariés — compagnon natif](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-30-FormalGroups-Native.ipynb) | BETA | Non | +| 65 | [Lean-31 : Euler et Navier–Stokes — reproduction pinée,…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-31-Euler-Navier-Stokes.ipynb) | BETA | Non | +| 66 | [Lean-33 : espaces de Schwartz — décroissance et…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-33-Distribution-Spaces.ipynb) | BETA | Non | +| 67 | [Lean-34 — Calculabilité et limites : de l'arrêt aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-34-Calculabilite-et-Limites.ipynb) | BETA | Non | +| 68 | [Lean-34b — FairBot par le théorème de Löb : coopérer…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-34b-FairBot-Loeb.ipynb) | BETA | Non | +| 69 | [Lean-36 : structures mathematiques finies — l'Annexe A…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-36-Structures-Finies-MUH-Lean.ipynb) | BETA | Non | +| 70 | [Lean-37 : Capstone — la sous-série « Serre 100 »](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-37-Capstone-Serre100.ipynb) | BETA | Non | +| 71 | [Corps finis et la borne de Hasse — distiller un…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/01-corps-finis-borne-hasse.ipynb) | BETA | Non | +| 72 | [2. Valeurs zêta multiples finies — l'anneau des adèles…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/02-valeurs-zeta-multiples-finies.ipynb) | BETA | Non | +| 73 | [Cohomologie de Čech calculée — espaces topologiques…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/03-cohomologie-cech-espaces-finis.ipynb) | BETA | Non | +| 74 | [Lemme de Yoneda calculé — catégories finies](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/04-lemme-yoneda-categories-finies.ipynb) | BETA | Non | +| 75 | [5. Tables de caractères — le squelette combinatoire…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/05-table-de-caracteres.ipynb) | BETA | Non | +| 76 | [Les bulles diaboliques de Minkowski — géométrie des…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/06-bulles-minkowski.ipynb) | BETA | Non | +| 77 | [Zéros de fonctions L, gaps et statistique GUE](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/07-zeros-fonctions-l-gaps-gue.ipynb) | BETA | Non | +| 78 | [Serre dans Mathlib — tour guidé des cinq monuments](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/08-serre-dans-mathlib.ipynb) | BETA | Non | +| 79 | [τ de Ramanujan — congruences, borne de Deligne, et la…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/09-congruences-tau-lacunarite-delta.ipynb) | BETA | Non | +| 80 | [10 — Empilements de sphères : la borne linéaire de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/10-empilements-borne-lp-cohn-elkies.ipynb) | BETA | Non | ## SymbolicAI/Planners (25 notebooks) @@ -184,7 +182,7 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | 24 | [Planners-11: Unified Planning](../../MyIA.AI.Notebooks/SymbolicAI/Planners/04-NeuroSymbolic/Planners-11-Unified-Planning.ipynb) | BETA | Oui | | 25 | [Planners-12: Learning to Plan avec LOOP](../../MyIA.AI.Notebooks/SymbolicAI/Planners/04-NeuroSymbolic/Planners-12-LOOP.ipynb) | BETA | Non | -## SymbolicAI/SMT (45 notebooks) +## SymbolicAI/SMT (46 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -206,17 +204,17 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | 16 | [10. Cryptarithmes (SEND + MORE = MONEY)](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-10-Cryptarithmetic-Python.ipynb) | BETA | Oui | | 17 | [11 - Coloration de Graphe avec Z3](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-11-Graph-Coloring-Python.ipynb) | BETA | Oui | | 18 | [12. Arithmetique reelle : raisonner sur les…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-12-Real-Arithmetic-Python.ipynb) | BETA | Oui | -| 19 | [14. Bit-vectors : verifier le debordement arithmetique](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-14-BitVectors-Overflow-Python.ipynb) | BETA | Oui | -| 20 | [15. Tableaux imbriqués et grilles 2D : carrés latins,…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-15-Nested-Arrays-2D-Python.ipynb) | BETA | Oui | -| 21 | [16. Meal-Planner déclaratif : du modèle Z3 au plan…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16-Meal-Planner-Python.ipynb) | BETA | Oui | -| 22 | [Z3-Python-16b — Meal-Planner : couche de données…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16b-Meal-Planner-Data-External-Python.ipynb) | BETA | Oui | -| 23 | [Z3-Python-16c — Meal-Planner : capstone patient…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16c-Meal-Planner-Patient-Capstone-Python.ipynb) | BETA | Oui | -| 24 | [Z3-Python-16d — Convergence à l'échelle : l'encodage…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16d-Meal-Planner-Convergence-Scale-Python.ipynb) | BETA | Oui | -| 25 | [Z3-Python-16e — Meal-Planner : l'optimisation (du SAT à…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16e-Meal-Planner-Optimize-Python.ipynb) | BETA | Oui | -| 26 | [Z3-Python 17 — Théorie des tableaux : Select, Store et…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-17-Array-Theory-Python.ipynb) | BETA | Oui | -| 27 | [Z3-Python 18 — Sudoku 4x4 : comparaison des modes Array…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-18-Sudoku-Modes-Python.ipynb) | BETA | Oui | -| 28 | [13. UNSAT cores : expliquer l'insatisfiabilite (le '…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-13-UnsatCores-Python.ipynb) | BETA | Oui | -| 29 | [Z3-Python-13b — UNSAT cores : le MUS (sous-ensemble irreductible)](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-13b-UnsatCores-MUS-Python.ipynb) | BETA | Oui | +| 19 | [13. UNSAT cores : expliquer l'insatisfiabilite (le '…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-13-UnsatCores-Python.ipynb) | BETA | Oui | +| 20 | [Z3-Python-13b — UNSAT cores : le MUS (sous-ensemble…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-13b-UnsatCores-MUS-Python.ipynb) | BETA | Oui | +| 21 | [14. Bit-vectors : verifier le debordement arithmetique](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-14-BitVectors-Overflow-Python.ipynb) | BETA | Oui | +| 22 | [15. Tableaux imbriqués et grilles 2D : carrés latins,…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-15-Nested-Arrays-2D-Python.ipynb) | BETA | Oui | +| 23 | [16. Meal-Planner déclaratif : du modèle Z3 au plan…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16-Meal-Planner-Python.ipynb) | BETA | Oui | +| 24 | [Z3-Python-16b — Meal-Planner : couche de données…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16b-Meal-Planner-Data-External-Python.ipynb) | BETA | Oui | +| 25 | [Z3-Python-16c — Meal-Planner : capstone patient…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16c-Meal-Planner-Patient-Capstone-Python.ipynb) | BETA | Oui | +| 26 | [Z3-Python-16d — Convergence à l'échelle : l'encodage…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16d-Meal-Planner-Convergence-Scale-Python.ipynb) | BETA | Oui | +| 27 | [Z3-Python-16e — Meal-Planner : l'optimisation (du SAT à…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-16e-Meal-Planner-Optimize-Python.ipynb) | BETA | Oui | +| 28 | [Z3-Python 17 — Théorie des tableaux : Select, Store et…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-17-Array-Theory-Python.ipynb) | BETA | Oui | +| 29 | [Z3-Python 18 — Sudoku 4x4 : comparaison des modes Array…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-API/Z3-18-Sudoku-Modes-Python.ipynb) | BETA | Oui | | 30 | [LINQ to Z3 - Résolution de Contraintes Déclarative](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/01_Linq2Z3_Intro.ipynb) | BETA | Oui | | 31 | [Sudoku : Théorème Explicite vs Modèle Implicite par…](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/02_Sudoku_Theorem_vs_Array.ipynb) | BETA | Oui | | 32 | [Sudoku 4x4 : comparaison des modes Array et Constants](../../MyIA.AI.Notebooks/SymbolicAI/SMT/Z3-Linq2Z3/03_Sudoku_Modes_Comparison.ipynb) | BETA | Oui | @@ -243,7 +241,7 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | 2 | [SW-1-Setup](../../MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-1-CSharp-Setup.ipynb) | BETA | Oui | | 3 | [SW-10-CSharp-RDFStar — Jumeau C# : annoter des triplets…](../../MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-10-CSharp-RDFStar.ipynb) | BETA | Oui | | 4 | [SW-10-Python-RDFStar](../../MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-10-Python-RDFStar.ipynb) | BETA | Oui | -| 5 | [SW-11-CSharp-KnowledgeGraphs](../../MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-11-CSharp-KnowledgeGraphs.ipynb) | BETA | Oui | +| 5 | [SW-11-CSharp-KnowledgeGraphs](../../MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-11-CSharp-KnowledgeGraphs.ipynb) | ALPHA | Oui | | 6 | [SW-11-Python-KnowledgeGraphs](../../MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-11-Python-KnowledgeGraphs.ipynb) | ALPHA | Oui | | 7 | [SW-12-Python-GraphRAG](../../MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-12-Python-GraphRAG.ipynb) | BETA | Non | | 8 | [SW-13-Reasoners](../../MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-13-Python-Reasoners.ipynb) | BETA | Oui | @@ -272,30 +270,30 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| -| 1 | [SC-00-Cypherpunk-Origins-Python - Les origines Cypherpunk de la…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-00-Cypherpunk-Origins-Python.ipynb) | BETA | Oui | -| 2 | [SC-01-Setup-Foundry-Python - Environnement Smart Contracts](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-01-Setup-Foundry-Python.ipynb) | BETA | Oui | +| 1 | [SC-00-Cypherpunk-Origins-Python - Les origines…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-00-Cypherpunk-Origins-Python.ipynb) | BETA | Oui | +| 2 | [SC-01-Setup-Foundry-Python - Environnement Smart…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-01-Setup-Foundry-Python.ipynb) | BETA | Oui | | 3 | [SC-02-Setup-Web3py-Python - Python et la Blockchain](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-02-Setup-Web3py-Python.ipynb) | BETA | Oui | | 4 | [SC-2b - Bac a sable institutionnel : des acteurs, pas…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/00-Foundations/SC-02b-Bac-ASable-Institutionnel-Python.ipynb) | BETA | Non | | 5 | [SC-03-Solidity-Basics-Python - Fondements de Solidity](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-03-Solidity-Basics-Python.ipynb) | BETA | Oui | | 6 | [SC-04-Functions-State-Python - Fonctions et État](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-04-Functions-State-Python.ipynb) | BETA | Oui | | 7 | [SC-05-Inheritance-Python - Heritage et Interfaces](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-05-Inheritance-Python.ipynb) | BETA | Oui | | 8 | [SC-06-Errors-Events-Python - Erreurs et Événements](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-06-Errors-Events-Python.ipynb) | BETA | Oui | -| 9 | [SC-10-Account-Abstraction-Python - ERC-4337 v0.9](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-10-Account-Abstraction-Python.ipynb) | BETA | Oui | -| 10 | [SC-11-LLM-Assisted-Python - Développement Smart Contracts…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-11-LLM-Assisted-Python.ipynb) | BETA | Non | -| 11 | [SC-07-Token-Standards-Python - Standards de Tokens](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-07-Token-Standards-Python.ipynb) | BETA | Oui | -| 12 | [SC-7b : ERC-20 + Lean — vérification formelle de…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-7b-ERC20-Lean-Verification-Companion.ipynb) | BETA | Non | -| 13 | [SC-7c : ERC-20 — compagnon natif Lean (kernel…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-07c-ERC20-Lean.ipynb) | ALPHA | Non | -| 14 | [SC-08-DeFi-Primitives-Python - Primitives DeFi](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-08-DeFi-Primitives-Python.ipynb) | BETA | Oui | -| 15 | [SC-09-DAO-Governance-Python - Gouvernance DAO](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-09-DAO-Governance-Python.ipynb) | BETA | Oui | +| 9 | [SC-07-Token-Standards-Python - Standards de Tokens](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-07-Token-Standards-Python.ipynb) | BETA | Oui | +| 10 | [SC-7c : ERC-20 — compagnon natif Lean (kernel…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-07c-ERC20-Lean.ipynb) | ALPHA | Non | +| 11 | [SC-08-DeFi-Primitives-Python - Primitives DeFi](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-08-DeFi-Primitives-Python.ipynb) | BETA | Oui | +| 12 | [SC-09-DAO-Governance-Python - Gouvernance DAO](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-09-DAO-Governance-Python.ipynb) | BETA | Oui | +| 13 | [SC-10-Account-Abstraction-Python - ERC-4337 v0.9](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-10-Account-Abstraction-Python.ipynb) | BETA | Oui | +| 14 | [SC-11-LLM-Assisted-Python - Développement Smart…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-11-LLM-Assisted-Python.ipynb) | BETA | Non | +| 15 | [SC-7b : ERC-20 + Lean — vérification formelle de…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-7b-ERC20-Lean-Verification-Companion.ipynb) | BETA | Non | | 16 | [SC-12-Foundry-Testing-Python - Tests avec Foundry](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/03-Foundry-Testing/SC-12-Foundry-Testing-Python.ipynb) | BETA | Non | | 17 | [SC-13-Fuzz-Invariants-Python - Fuzz Testing](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/03-Foundry-Testing/SC-13-Fuzz-Invariants-Python.ipynb) | BETA | Oui | | 18 | [SC-14-Formal-Vérification - Vérification Formelle](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/03-Foundry-Testing/SC-14-Formal-Verification-Python.ipynb) | BETA | Non | -| 19 | [SC-15-Zero-Knowledge-Proofs-Python - Preuves a Divulgation…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-15-Zero-Knowledge-Proofs-Python.ipynb) | BETA | Oui | +| 19 | [SC-15-Zero-Knowledge-Proofs-Python - Preuves a…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-15-Zero-Knowledge-Proofs-Python.ipynb) | BETA | Oui | | 20 | [SC-16-Homomorphic-Encryption-Python - Chiffrement…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-16-Homomorphic-Encryption-Python.ipynb) | BETA | Oui | | 21 | [SC-17-E2E-Verifiable-Voting-Python - Vote Electronique…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/04-Privacy-Cryptography/SC-17-E2E-Verifiable-Voting-Python.ipynb) | BETA | Oui | | 22 | [SC-18-Vyper-Python - Smart Contracts en Python-like](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-18-Vyper-Python.ipynb) | BETA | Oui | -| 23 | [SC-19-Ripple-XRP-Python - Protocole Ripple et XRP Ledger](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-19-Ripple-XRP-Python.ipynb) | BETA | Oui | -| 24 | [SC-20-Bitcoin-Scripting-Python - Bitcoin, UTXO et Scripts](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-20-Bitcoin-Scripting-Python.ipynb) | BETA | Non | +| 23 | [SC-19-Ripple-XRP-Python - Protocole Ripple et XRP…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-19-Ripple-XRP-Python.ipynb) | BETA | Oui | +| 24 | [SC-20-Bitcoin-Scripting-Python - Bitcoin, UTXO et…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-20-Bitcoin-Scripting-Python.ipynb) | BETA | Non | | 25 | [SC-21-Move-Sui-Python - Move sur Sui](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-21-Move-Sui-Python.ipynb) | BETA | Oui | | 26 | [SC-22-Solana-Anchor-Python - Solana avec Anchor](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/05-Alternative-Chains/SC-22-Solana-Anchor-Python.ipynb) | BETA | Oui | | 27 | [SC-23-Cross-Chain-Python - Interoperabilite Cross-Chain](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/06-Real-World/SC-23-Cross-Chain-Python.ipynb) | BETA | Oui | @@ -304,7 +302,7 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | 30 | [SC-26 : Projet Final - DApp Complete](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/06-Real-World/SC-26-Final-Project-Python.ipynb) | BETA | Oui | | 31 | [SC-27 : Dette d'irréversibilité — la boucle de…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/06-Real-World/SC-27-Dette-Irreversibilite-Python.ipynb) | BETA | Oui | -## SymbolicAI/SymbolicLearning (26 notebooks) +## SymbolicAI/SymbolicLearning (27 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -317,23 +315,24 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | 7 | [SL-12b-PavlovDLS-Reproduction — artefact Pavlov (DLS…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-12b-PavlovDLS-Reproduction.ipynb) | BETA | Oui | | 8 | [SL-12b : Synthèse logique spectrale — Fourier booléen…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-12b-SpectralLogicSynthesis.ipynb) | BETA | Oui | | 9 | [SL-13 : DISCOVER léger — diagnostic de structure TPR…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-13-Discover-TPR.ipynb) | BETA | Non | -| 10 | [SL-14 — AI Feynman : découvrir des équations](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-14-AIFeynman-Discover-Equations.ipynb) | BETA | Oui | -| 11 | [SL-15 — Conjectures apprises pour un vérificateur…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-15-LearnedConjectures-Solver.ipynb) | BETA | Oui | -| 12 | [SL-1b — Apprentissage PAC formellement : le lake…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-1b-LogicalLearning-Lean-Native.ipynb) | BETA | Non | -| 13 | [SL-2 - Apprentissage et Connaissance : EBL & RBL (C#)](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-2-KnowledgeBasedLearning-Csharp.ipynb) | ALPHA | Oui | -| 14 | [SL-2 --- Apprentissage et Connaissance (EBL & RBL)](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-2-KnowledgeBasedLearning.ipynb) | BETA | Oui | -| 15 | [SL-3 — Apprentissage basé sur la pertinence (twin C#…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-3-RelevanceLearning-Csharp.ipynb) | BETA | Oui | -| 16 | [SL-3 --- Apprentissage Base sur la Pertinence (RBL…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-3-RelevanceLearning.ipynb) | BETA | Oui | -| 17 | [SL-4 — Programmation Logique Inductive (ILP) — Twin C#…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-4-InductiveLogicProgramming-Csharp.ipynb) | BETA | Oui | -| 18 | [SL-4 --- Programmation Logique Inductive (ILP)](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-4-InductiveLogicProgramming.ipynb) | BETA | Non | -| 19 | [SL-5 - Resolution Inverse & ILP (C#)](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-5-InverseResolution-Csharp.ipynb) | ALPHA | Oui | -| 20 | [SL-5 --- Resolution Inverse et Progol (ILP bottom-up)](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-5-InverseResolution.ipynb) | BETA | Oui | -| 21 | [SL-6 (C#) : Moteurs ILP modernes — apprendre des…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-6-ModernILP-Csharp.ipynb) | BETA | Oui | -| 22 | [SL-6 --- Moteurs ILP modernes : Aleph, Metagol, Popper…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-6-ModernILP.ipynb) | BETA | Non | -| 23 | [SL-7 : Integration Neuro-Symbolique](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-7-NeuroSymbolic.ipynb) | BETA | Non | -| 24 | [SL-8 (C#) : ILP Moderne et Knowledge Graphs](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-8-KnowledgeGraphs-ILP-Csharp.ipynb) | BETA | Oui | -| 25 | [SL-8 - ILP Moderne et Knowledge Graphs](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-8-KnowledgeGraphs-ILP.ipynb) | BETA | Oui | -| 26 | [SL-9 - LLMs et Apprentissage Symbolique : Generation et…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-9-LLM-SymbolicLearning.ipynb) | BETA | Non | +| 10 | [SL-13b : TPR x SAE — deux lectures des mêmes états…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-13b-TPR-SAE.ipynb) | BETA | Non | +| 11 | [SL-14 — AI Feynman : découvrir des équations](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-14-AIFeynman-Discover-Equations.ipynb) | BETA | Oui | +| 12 | [SL-15 — Conjectures apprises pour un vérificateur…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-15-LearnedConjectures-Solver.ipynb) | BETA | Oui | +| 13 | [SL-1b — Apprentissage PAC formellement : le lake…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-1b-LogicalLearning-Lean-Native.ipynb) | BETA | Non | +| 14 | [SL-2 - Apprentissage et Connaissance : EBL & RBL (C#)](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-2-KnowledgeBasedLearning-Csharp.ipynb) | ALPHA | Oui | +| 15 | [SL-2 --- Apprentissage et Connaissance (EBL & RBL)](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-2-KnowledgeBasedLearning.ipynb) | BETA | Oui | +| 16 | [SL-3 — Apprentissage basé sur la pertinence (twin C#…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-3-RelevanceLearning-Csharp.ipynb) | BETA | Oui | +| 17 | [SL-3 --- Apprentissage Base sur la Pertinence (RBL…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-3-RelevanceLearning.ipynb) | BETA | Oui | +| 18 | [SL-4 — Programmation Logique Inductive (ILP) — Twin C#…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-4-InductiveLogicProgramming-Csharp.ipynb) | BETA | Oui | +| 19 | [SL-4 --- Programmation Logique Inductive (ILP)](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-4-InductiveLogicProgramming.ipynb) | BETA | Non | +| 20 | [SL-5 - Resolution Inverse & ILP (C#)](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-5-InverseResolution-Csharp.ipynb) | ALPHA | Oui | +| 21 | [SL-5 --- Resolution Inverse et Progol (ILP bottom-up)](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-5-InverseResolution.ipynb) | BETA | Oui | +| 22 | [SL-6 (C#) : Moteurs ILP modernes — apprendre des…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-6-ModernILP-Csharp.ipynb) | BETA | Oui | +| 23 | [SL-6 --- Moteurs ILP modernes : Aleph, Metagol, Popper…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-6-ModernILP.ipynb) | BETA | Non | +| 24 | [SL-7 : Integration Neuro-Symbolique](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-7-NeuroSymbolic.ipynb) | BETA | Non | +| 25 | [SL-8 (C#) : ILP Moderne et Knowledge Graphs](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-8-KnowledgeGraphs-ILP-Csharp.ipynb) | BETA | Oui | +| 26 | [SL-8 - ILP Moderne et Knowledge Graphs](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-8-KnowledgeGraphs-ILP.ipynb) | BETA | Oui | +| 27 | [SL-9 - LLMs et Apprentissage Symbolique : Generation et…](../../MyIA.AI.Notebooks/SymbolicAI/SymbolicLearning/SL-9-LLM-SymbolicLearning.ipynb) | BETA | Non | ## SymbolicAI/Tweety (39 notebooks) diff --git a/docs/curriculum/recherche.md b/docs/curriculum/recherche.md index 6b5b9dd546..3810bf5197 100644 --- a/docs/curriculum/recherche.md +++ b/docs/curriculum/recherche.md @@ -20,109 +20,110 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | Métrique | Valeur | |----------|--------| -| Notebooks | 291 | +| Notebooks | 295 | | PRODUCTION | 0 | -| BETA | 282 | -| ALPHA | 9 | +| BETA | 285 | +| ALPHA | 10 | -## GameTheory (94 notebooks) +## GameTheory (95 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| -| 1 | [GameTheory-01-Setup](../../MyIA.AI.Notebooks/GameTheory/GameTheory-01-Setup-Python.ipynb) | BETA | Non | -| 2 | [GameTheory-2 (Part 2) : Support Enumeration — Équilibre…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm-Part2-CSharp.ipynb) | BETA | Oui | -| 3 | [GameTheory-2 : Jeux sous forme normale (C# / .NET) —…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm-CSharp.ipynb) | BETA | Oui | +| 1 | [GameTheory-01-Setup-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-01-Setup-Python.ipynb) | BETA | Non | +| 2 | [GameTheory-2 : Jeux sous forme normale (C# / .NET) —…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm-CSharp.ipynb) | BETA | Oui | +| 3 | [GameTheory-2 (Part 2) : Support Enumeration — Équilibre…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm-Part2-CSharp.ipynb) | BETA | Oui | | 4 | [GameTheory-2 (Part 2) : Support Enumeration — Équilibre…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm-Part2-Python.ipynb) | BETA | Oui | -| 5 | [GameTheory-02-NormalForm](../../MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm-Python.ipynb) | BETA | Oui | +| 5 | [GameTheory-02-NormalForm-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-02-NormalForm-Python.ipynb) | BETA | Oui | | 6 | [GameTheory 2b - Formalisation Lean : Definitions de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-02b-Lean-Definitions-Lean.ipynb) | BETA | Non | | 7 | [GameTheory-02c : Traveler's Dilemma en C# — le twin qui…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-02c-Travelers-Dilemma-CSharp.ipynb) | BETA | Oui | -| 8 | [GameTheory-02c-Travelers-Dilemma](../../MyIA.AI.Notebooks/GameTheory/GameTheory-02c-Travelers-Dilemma-Python.ipynb) | BETA | Oui | +| 8 | [GameTheory-02c-Travelers-Dilemma-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-02c-Travelers-Dilemma-Python.ipynb) | BETA | Oui | | 9 | [GameTheory-3 : Topologie des Jeux 2×2 — Twin C#…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-03-Topology2x2-CSharp.ipynb) | BETA | Oui | -| 10 | [GameTheory-03-Topology2x2](../../MyIA.AI.Notebooks/GameTheory/GameTheory-03-Topology2x2-Python.ipynb) | BETA | Oui | -| 11 | [GameTheory-3a — Chemins de swaps : à quelle distance…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-03b-Chemins-de-Swaps-Lean-Python.ipynb) | BETA | Oui | +| 10 | [GameTheory-03-Topology2x2-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-03-Topology2x2-Python.ipynb) | BETA | Oui | +| 11 | [GameTheory-3a — Chemins de swaps : à quelle distance…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-03b-Chemins-de-Swaps-Lean-Python.ipynb) | BETA | Non | | 12 | [GameTheory 3b : Chambres, murs, codimension — les jeux…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-03c-Chambres-et-Murs-Python.ipynb) | BETA | Oui | | 13 | [GameTheory-3c — Le joueur LLM dans le tableau…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-03d-Le-Joueur-LLM-Python.ipynb) | BETA | Non | | 14 | [GameTheory-03d — Biens publics non-lineaires : plan de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-03e-Plan-de-deformation-Python.ipynb) | BETA | Oui | | 15 | [GameTheory 3e : Meta-Actions Tarifees et Parcours…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-03f-Meta-Actions-Tarifees-Python.ipynb) | BETA | Oui | | 16 | [GameTheory-03h — Deux espèces de flèches : quand une…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-03g-Deux-Especes-de-Fleches-Python.ipynb) | BETA | Oui | -| 17 | [GameTheory-04-NashEquilibrium (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-04-NashEquilibrium-CSharp.ipynb) | BETA | Oui | -| 18 | [GameTheory-04-NashEquilibrium](../../MyIA.AI.Notebooks/GameTheory/GameTheory-04-NashEquilibrium-Python.ipynb) | BETA | Oui | +| 17 | [GameTheory-04-NashEquilibrium-Python (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-04-NashEquilibrium-CSharp.ipynb) | BETA | Oui | +| 18 | [GameTheory-04-NashEquilibrium-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-04-NashEquilibrium-Python.ipynb) | BETA | Oui | | 19 | [GameTheory 4b - Theoreme d'Existence de Nash (Lean)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-04b-Lean-NashExistence-Lean.ipynb) | BETA | Non | | 20 | [GameTheory 4c - Théorème d'Existence de Nash (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-04c-NashExistence-CSharp.ipynb) | ALPHA | Oui | | 21 | [GameTheory 4c - Theoreme d'Existence de Nash (Python)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-04c-NashExistence-Python.ipynb) | BETA | Non | -| 22 | [GameTheory-04d-Marchandage-Asymetrique](../../MyIA.AI.Notebooks/GameTheory/GameTheory-04d-Marchandage-Asymetrique-Python.ipynb) | BETA | Oui | +| 22 | [GameTheory-04d-Marchandage-Asymetrique-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-04d-Marchandage-Asymetrique-Python.ipynb) | ALPHA | Oui | | 23 | [GameTheory 04e — Oracles réflexifs, décision causale et…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-04e-Reflective-Oracles-Python.ipynb) | BETA | Oui | | 24 | [GameTheory 04f — Théories de la décision face à un…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-04f-Theories-Decision-Predicteur-Python.ipynb) | BETA | Oui | -| 25 | [GameTheory-05-ZeroSum-Minimax (Twin C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-05-ZeroSum-Minimax-CSharp.ipynb) | BETA | Oui | -| 26 | [GameTheory-05-ZeroSum-Minimax](../../MyIA.AI.Notebooks/GameTheory/GameTheory-05-ZeroSum-Minimax-Python.ipynb) | BETA | Oui | +| 25 | [GameTheory-05-ZeroSum-Minimax-Python (Twin C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-05-ZeroSum-Minimax-CSharp.ipynb) | BETA | Oui | +| 26 | [GameTheory-05-ZeroSum-Minimax-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-05-ZeroSum-Minimax-Python.ipynb) | BETA | Oui | | 27 | [GameTheory-5b — Théorème minimax de von Neumann…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-05b-Lean-Minimax-Lean.ipynb) | BETA | Non | | 28 | [GameTheory-6 : Évolution et Confiance — Twin C#…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06-EvolutionTrust-CSharp.ipynb) | BETA | Oui | -| 29 | [GameTheory-06-EvolutionTrust](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06-EvolutionTrust-Python.ipynb) | BETA | Oui | +| 29 | [GameTheory-06-EvolutionTrust-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06-EvolutionTrust-Python.ipynb) | BETA | Oui | | 30 | [GameTheory-6c (C#) : Jeux Répétés et Théorème Folk](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06c-RepeatedGames-FolkTheorem-CSharp.ipynb) | BETA | Oui | | 31 | [GameTheory-6c : Jeux Répétés et Théorème Folk (Folk…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06c-RepeatedGames-FolkTheorem-Python.ipynb) | BETA | Oui | | 32 | [GameTheory-06d : Sympathie contre Engagement — la…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06d-Sympathie-vs-Engagement-Python.ipynb) | BETA | Oui | | 33 | [GameTheory-06e : Transparence des programmes et issue…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06e-Open-Source-Game-Theory-Python.ipynb) | ALPHA | Oui | -| 34 | [GameTheory-06f — Preuves bornees et cout du…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06j-Bounded-Proofs-Reasoning-Costs-Python.ipynb) | BETA | Oui | +| 34 | [GameTheory-06g — Agents à budget explicite (companion…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06f-Bounded-Agents-Lean.ipynb) | BETA | Non | | 35 | [GameTheory-06g — Équilibres de jeux-programmes fondés…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06g-Simulation-Based-Program-Equilibria-Python.ipynb) | BETA | Oui | | 36 | [GameTheory-06h — Programmes transparents comme…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06h-Transparent-Institutions-Python.ipynb) | BETA | Oui | -| 37 | [GameTheory-07-ExtensiveForm (Twin C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-07-ExtensiveForm-CSharp.ipynb) | BETA | Oui | -| 38 | [GameTheory-07-ExtensiveForm](../../MyIA.AI.Notebooks/GameTheory/GameTheory-07-ExtensiveForm-Python.ipynb) | BETA | Oui | -| 39 | [GameTheory-08-CombinatorialGames (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08-CombinatorialGames-CSharp.ipynb) | BETA | Oui | -| 40 | [GameTheory 8 - Jeux Combinatoires](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08-CombinatorialGames-Python.ipynb) | BETA | Oui | -| 41 | [GameTheory 8b - Jeux Combinatoires en Lean](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08b-Lean-CombinatorialGames-Lean.ipynb) | BETA | Non | -| 42 | [GameTheory 8c - Jeux Combinatoires : Approfondissement…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08c-CombinatorialGames-CSharp.ipynb) | BETA | Oui | -| 43 | [GameTheory 8c - Jeux Combinatoires : Approfondissement…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08c-CombinatorialGames-Python.ipynb) | BETA | Oui | -| 44 | [GameTheory 8d - Combinatorial Games natif : le lake…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08d-Lean-CGT-Lean.ipynb) | BETA | Non | -| 45 | [GameTheory-09-BackwardInduction (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09-BackwardInduction-CSharp.ipynb) | BETA | Oui | -| 46 | [GameTheory-09-BackwardInduction](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09-BackwardInduction-Python.ipynb) | BETA | Oui | -| 47 | [Stackelberg : la performativité sans mystère](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09b-Commitment-Stackelberg-Python.ipynb) | BETA | Oui | -| 48 | [GameTheory-09c : Stackelberg Security Game —…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09c-Stackelberg-SecurityGame-Python.ipynb) | BETA | Oui | -| 49 | [GameTheory-10 — Équilibres Parfaits de Sous-Jeux et…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-10-ForwardInduction-SPE-CSharp.ipynb) | BETA | Oui | -| 50 | [GameTheory-10-ForwardInduction-SPE](../../MyIA.AI.Notebooks/GameTheory/GameTheory-10-ForwardInduction-SPE-Python.ipynb) | BETA | Oui | -| 51 | [GameTheory-11-BayesianGames-Csharp](../../MyIA.AI.Notebooks/GameTheory/GameTheory-11-BayesianGames-CSharp.ipynb) | BETA | Oui | -| 52 | [GameTheory-11-BayesianGames](../../MyIA.AI.Notebooks/GameTheory/GameTheory-11-BayesianGames-Python.ipynb) | BETA | Oui | -| 53 | [GameTheory-11b — Jeux Bayésiens en Lean 4 (companion)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-11b-Lean-BayesianGamesExt-Lean.ipynb) | BETA | Non | -| 54 | [GameTheory-12 — Jeux de Réputation (twin C# du notebook…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-12-ReputationGames-CSharp.ipynb) | BETA | Oui | -| 55 | [GameTheory-12-ReputationGames](../../MyIA.AI.Notebooks/GameTheory/GameTheory-12-ReputationGames-Python.ipynb) | BETA | Oui | -| 56 | [GameTheory-13 : Jeux a Information Imparfaite et CFR…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13-ImperfectInfo-CFR-CSharp.ipynb) | BETA | Oui | -| 57 | [GameTheory-13 : Jeux a Information Imparfaite et CFR](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13-ImperfectInfo-CFR-Python.ipynb) | BETA | Non | -| 58 | [GameTheory-13b : Safe Subgame Solving -- quand le…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13b-Safe-Subgame-Solving-Python.ipynb) | BETA | Oui | -| 59 | [GameTheory-13c : Safe Subgame Solving en C# — le twin…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13c-Safe-Subgame-Solving-CSharp.ipynb) | BETA | Oui | -| 60 | [GameTheory-13d : Optimistic Counterfactual Regret…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13d-Optimistic-CFR-Python.ipynb) | BETA | Oui | -| 61 | [GameTheory-14 : Jeux Differentiels et Equilibres de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames-CSharp.ipynb) | BETA | Oui | -| 62 | [GameTheory-14 : Jeux Differentiels et Equilibres de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames-Python.ipynb) | BETA | Oui | -| 63 | [GameTheory-15 — Jeux Coopératifs (Twin C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames-CSharp.ipynb) | BETA | Oui | -| 64 | [GameTheory-15-CooperativeGames](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames-Python.ipynb) | BETA | Oui | -| 65 | [GameTheory 15b - Jeux Cooperatifs en Lean :…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15b-Lean-CooperativeGames-Lean.ipynb) | BETA | Non | -| 66 | [GameTheory 15c - Jeux Cooperatifs (C# / .NET)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-CSharp.ipynb) | BETA | Oui | -| 67 | [GameTheory 15c - Jeux Cooperatifs Lean (Python)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-Python.ipynb) | BETA | Oui | -| 68 | [GameTheory 15d - La decomposition de Mobius sur le…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15d-Mobius-Coalitions-Lean-Python.ipynb) | BETA | Oui | -| 69 | [GameTheory-15e — Pouvoir coalitionnel : calcul, SMT…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15e-Coalition-Power-SMT-Python.ipynb) | BETA | Oui | -| 70 | [GameTheory 15f - Valeur de Shapley de groupe : évaluer…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15f-Shapley-Groupes-Python.ipynb) | BETA | Oui | -| 71 | [GameTheory 15g - Assistance Games (résultat 2026)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15g-AssistanceGames-2026-Python.ipynb) | BETA | Oui | -| 72 | [GameTheory-16-MechanismDesign (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign-CSharp.ipynb) | BETA | Oui | -| 73 | [GameTheory-16 : Théorie des Mécanismes et Principe de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign-Python.ipynb) | BETA | Oui | -| 74 | [GameTheory-16b : Automated Mechanism Design (AMD)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16b-Automated-Mechanism-Design-Python.ipynb) | BETA | Oui | -| 75 | [GameTheory-16c : La dimension paiement que le designer…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16c-Extraction-de-Revenu-DSIC-IR-Python.ipynb) | BETA | Oui | -| 76 | [GameTheory-16d — L'echange de reins : de la valeur…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16d-Echange-de-Reins-Lean-Python.ipynb) | BETA | Oui | -| 77 | [GameTheory-16e : Pilote — joueurs LLM hétérogènes sur…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16e-LLM-Players-Othman-Sandholm-Python.ipynb) | BETA | Non | -| 78 | [GameTheory-17 (C#) : Multi-Agent Reinforcement Learning…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL-CSharp.ipynb) | BETA | Oui | -| 79 | [GameTheory-17 : Apprentissage par Renforcement…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL-Python.ipynb) | BETA | Oui | -| 80 | [Information asymétrique : types privés, antisélection…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17b-Asymmetric-Information-Python.ipynb) | BETA | Oui | -| 81 | [Le marché des lemons : le certificat formel exécuté](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17c-Lean-Lemons-Certificat-Lean.ipynb) | BETA | Non | -| 82 | [Du marché au bilan : le pont théorie des jeux théorie…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17f-Market-to-Balance-Sheet-Python.ipynb) | BETA | Oui | -| 83 | [Screening, signal et anticipation : les trois réponses…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17d-Lean-Screening-Signaling-Lean.ipynb) | BETA | Non | -| 84 | [GameTheory-18 : Open Games et Lentilles -- la…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18-Open-Games-et-Lentilles-Python.ipynb) | BETA | Oui | -| 85 | [GameTheory-18b : Casser la composition — où la…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18b-Casser-la-Composition-Python.ipynb) | BETA | Oui | -| 86 | [GameTheory-19 : L'abstraction a dette mesurable](../../MyIA.AI.Notebooks/GameTheory/GameTheory-19-Abstraction-a-Dette-Python.ipynb) | BETA | Oui | -| 87 | [GameTheory 24b : Le temoin d'impossibilite](../../MyIA.AI.Notebooks/GameTheory/GameTheory-20b-Chemin-Minimal-Temoins-Impossibilite-Python.ipynb) | BETA | Oui | -| 88 | [GameTheory 20c : Le chemin minimal sur un second…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-20c-Chemin-Minimal-3x2-Ordinal-Python.ipynb) | BETA | Oui | -| 89 | [GameTheory-21 — Loi II, seconde jambe : synthétiser un…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-20d-Loi-II-Translateur-Life-Python.ipynb) | BETA | Oui | -| 90 | [GameTheory-22 — Ensembles limites : Poincaré-Bendixson…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06i-Ensembles-Limites-Poincare-Bendixson-Python.ipynb) | BETA | Oui | -| 91 | [GameTheory-23 — L'algorithme de Kuhn-Munkres :…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16f-Munkres-Assignment-Python.ipynb) | BETA | Oui | -| 92 | [GameTheory 23b — Le lake assignment_lean par son…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16f-Lean-Assignment-Lean.ipynb) | BETA | Non | -| 93 | [GameTheory-24 : Banc de calibration — humour, forme…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18c-Humour-Banc-Python.ipynb) | BETA | Oui | -| 94 | [GameTheory-24b : Banc humour — passer à l'échelle](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18d-Humour-Banc-Dur-Python.ipynb) | BETA | Non | +| 37 | [GameTheory-06i — Ensembles limites : Poincaré-Bendixson…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06i-Ensembles-Limites-Poincare-Bendixson-Python.ipynb) | BETA | Oui | +| 38 | [GameTheory-06f — Preuves bornees et cout du…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06j-Bounded-Proofs-Reasoning-Costs-Python.ipynb) | BETA | Oui | +| 39 | [GameTheory-07-ExtensiveForm-Python (Twin C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-07-ExtensiveForm-CSharp.ipynb) | BETA | Oui | +| 40 | [GameTheory-07-ExtensiveForm-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-07-ExtensiveForm-Python.ipynb) | BETA | Oui | +| 41 | [GameTheory 8 - Jeux Combinatoires (Twin C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08-CombinatorialGames-CSharp.ipynb) | BETA | Oui | +| 42 | [GameTheory 8 - Jeux Combinatoires](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08-CombinatorialGames-Python.ipynb) | BETA | Oui | +| 43 | [GameTheory 8b - Jeux Combinatoires en Lean](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08b-Lean-CombinatorialGames-Lean.ipynb) | BETA | Non | +| 44 | [GameTheory 8c - Jeux Combinatoires : Approfondissement…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08c-CombinatorialGames-CSharp.ipynb) | BETA | Oui | +| 45 | [GameTheory 8c - Jeux Combinatoires : Approfondissement…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08c-CombinatorialGames-Python.ipynb) | BETA | Oui | +| 46 | [GameTheory 8d - Combinatorial Games natif : le lake…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08d-Lean-CGT-Lean.ipynb) | BETA | Non | +| 47 | [GameTheory-09-BackwardInduction-Python (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09-BackwardInduction-CSharp.ipynb) | BETA | Oui | +| 48 | [GameTheory-09-BackwardInduction-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09-BackwardInduction-Python.ipynb) | BETA | Oui | +| 49 | [Stackelberg : la performativité sans mystère](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09b-Commitment-Stackelberg-Python.ipynb) | BETA | Oui | +| 50 | [GameTheory-09c : Stackelberg Security Game —…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09c-Stackelberg-SecurityGame-Python.ipynb) | BETA | Oui | +| 51 | [GameTheory-10 — Équilibres Parfaits de Sous-Jeux et…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-10-ForwardInduction-SPE-CSharp.ipynb) | BETA | Oui | +| 52 | [GameTheory-10-ForwardInduction-SPE-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-10-ForwardInduction-SPE-Python.ipynb) | BETA | Oui | +| 53 | [GameTheory-11-BayesianGames-CSharp](../../MyIA.AI.Notebooks/GameTheory/GameTheory-11-BayesianGames-CSharp.ipynb) | BETA | Oui | +| 54 | [GameTheory-11-BayesianGames-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-11-BayesianGames-Python.ipynb) | BETA | Oui | +| 55 | [GameTheory-11b — Jeux Bayésiens en Lean 4 (companion)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-11b-Lean-BayesianGamesExt-Lean.ipynb) | BETA | Non | +| 56 | [GameTheory-12 — Jeux de Réputation (twin C# du notebook…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-12-ReputationGames-CSharp.ipynb) | BETA | Oui | +| 57 | [GameTheory-12-ReputationGames-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-12-ReputationGames-Python.ipynb) | BETA | Oui | +| 58 | [GameTheory-13 : Jeux a Information Imparfaite et CFR…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13-ImperfectInfo-CFR-CSharp.ipynb) | BETA | Oui | +| 59 | [GameTheory-13 : Jeux a Information Imparfaite et CFR](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13-ImperfectInfo-CFR-Python.ipynb) | BETA | Non | +| 60 | [GameTheory-13b : Safe Subgame Solving -- quand le…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13b-Safe-Subgame-Solving-Python.ipynb) | BETA | Oui | +| 61 | [GameTheory-13c : Safe Subgame Solving en C# — le twin…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13c-Safe-Subgame-Solving-CSharp.ipynb) | BETA | Oui | +| 62 | [GameTheory-13d : Optimistic Counterfactual Regret…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13d-Optimistic-CFR-Python.ipynb) | BETA | Oui | +| 63 | [GameTheory-14 : Jeux Differentiels et Equilibres de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames-CSharp.ipynb) | BETA | Oui | +| 64 | [GameTheory-14 : Jeux Differentiels et Equilibres de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames-Python.ipynb) | BETA | Oui | +| 65 | [GameTheory-15 — Jeux Coopératifs (Twin C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames-CSharp.ipynb) | BETA | Oui | +| 66 | [GameTheory-15-CooperativeGames-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames-Python.ipynb) | BETA | Oui | +| 67 | [GameTheory 15b - Jeux Cooperatifs en Lean :…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15b-Lean-CooperativeGames-Lean.ipynb) | BETA | Non | +| 68 | [GameTheory 15c - Jeux Cooperatifs (C# / .NET)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-CSharp.ipynb) | BETA | Oui | +| 69 | [GameTheory 15c - Jeux Cooperatifs Lean (Python)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-Python.ipynb) | BETA | Oui | +| 70 | [GameTheory 15d - La decomposition de Mobius sur le…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15d-Mobius-Coalitions-Lean-Python.ipynb) | BETA | Non | +| 71 | [GameTheory-15e — Pouvoir coalitionnel : calcul, SMT…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15e-Coalition-Power-SMT-Python.ipynb) | BETA | Oui | +| 72 | [GameTheory 15f - Valeur de Shapley de groupe : évaluer…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15f-Shapley-Groupes-Python.ipynb) | BETA | Oui | +| 73 | [GameTheory 15g - Assistance Games (résultat 2026)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15g-AssistanceGames-2026-Python.ipynb) | BETA | Oui | +| 74 | [GameTheory-16-MechanismDesign-Python (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign-CSharp.ipynb) | BETA | Oui | +| 75 | [GameTheory-16 : Théorie des Mécanismes et Principe de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign-Python.ipynb) | BETA | Oui | +| 76 | [GameTheory-16b : Automated Mechanism Design (AMD)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16b-Automated-Mechanism-Design-Python.ipynb) | BETA | Oui | +| 77 | [GameTheory-16c : La dimension paiement que le designer…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16c-Extraction-de-Revenu-DSIC-IR-Python.ipynb) | BETA | Oui | +| 78 | [GameTheory-16d — L'echange de reins : de la valeur…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16d-Echange-de-Reins-Lean-Python.ipynb) | BETA | Non | +| 79 | [GameTheory-16e : Pilote — joueurs LLM hétérogènes sur…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16e-LLM-Players-Othman-Sandholm-Python.ipynb) | BETA | Non | +| 80 | [GameTheory 23b — Le lake assignment_lean par son…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16f-Lean-Assignment-Lean.ipynb) | BETA | Non | +| 81 | [GameTheory-23 — L'algorithme de Kuhn-Munkres :…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16f-Munkres-Assignment-Python.ipynb) | BETA | Oui | +| 82 | [GameTheory-17 (C#) : Multi-Agent Reinforcement Learning…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL-CSharp.ipynb) | BETA | Oui | +| 83 | [GameTheory-17 : Apprentissage par Renforcement…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL-Python.ipynb) | BETA | Oui | +| 84 | [Information asymétrique : types privés, antisélection…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17b-Asymmetric-Information-Python.ipynb) | BETA | Oui | +| 85 | [Le marché des lemons : le certificat formel exécuté](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17c-Lean-Lemons-Certificat-Lean.ipynb) | BETA | Non | +| 86 | [Screening, signal et anticipation : les trois réponses…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17d-Lean-Screening-Signaling-Lean.ipynb) | BETA | Non | +| 87 | [Du marché au bilan : le pont théorie des jeux théorie…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17f-Market-to-Balance-Sheet-Python.ipynb) | BETA | Oui | +| 88 | [GameTheory-18 : Open Games et Lentilles -- la…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18-Open-Games-et-Lentilles-Python.ipynb) | BETA | Oui | +| 89 | [GameTheory-18b : Casser la composition — où la…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18b-Casser-la-Composition-Python.ipynb) | BETA | Oui | +| 90 | [GameTheory-24 : Banc de calibration — humour, forme…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18c-Humour-Banc-Python.ipynb) | BETA | Oui | +| 91 | [GameTheory-18d : Banc humour — passer à l'échelle](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18d-Humour-Banc-Dur-Python.ipynb) | BETA | Non | +| 92 | [GameTheory-19 : L'abstraction a dette mesurable](../../MyIA.AI.Notebooks/GameTheory/GameTheory-19-Abstraction-a-Dette-Python.ipynb) | BETA | Oui | +| 93 | [GameTheory 24b : Le temoin d'impossibilite](../../MyIA.AI.Notebooks/GameTheory/GameTheory-20b-Chemin-Minimal-Temoins-Impossibilite-Python.ipynb) | BETA | Oui | +| 94 | [GameTheory 20c : Le chemin minimal sur un second…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-20c-Chemin-Minimal-3x2-Ordinal-Python.ipynb) | BETA | Oui | +| 95 | [GameTheory-21 — Loi II, seconde jambe : synthétiser un…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-20d-Loi-II-Translateur-Life-Python.ipynb) | BETA | Oui | ## GameTheory/SocialChoice (10 notebooks) @@ -150,7 +151,7 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | 5 | [IIT-5. Les lentilles de conscience comme bancs de…](../../MyIA.AI.Notebooks/IIT/IIT-05-Lentilles-et-Dissociations.ipynb) | BETA | Oui | | 6 | [IIT-6. L'objet qui a mordu IIT — l'expander à Φ énorme,…](../../MyIA.AI.Notebooks/IIT/IIT-06-L-Objet-qui-a-Mordu-IIT.ipynb) | BETA | Oui | -## IIT/ICT-Series (73 notebooks) +## IIT/ICT-Series (75 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -191,7 +192,7 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | 35 | [ICT-19b — Raffinement et résolution des stubs (tranche…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-19b-EnjeuBattery-Raffinement-Python.ipynb) | BETA | Non | | 36 | [ICT-20 — FeatureCatastrophes : *calibration de méthode*](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-20-FeatureCatastrophes-Python.ipynb) | BETA | Non | | 37 | [ICT-21 — SAETrajectoires : le substrat S4 entre au banc](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-21-SAETrajectoires-Python.ipynb) | BETA | Non | -| 38 | [ICT-21b-SAECalibration-Python — que reconstruit réellement…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-21b-SAECalibration-Python.ipynb) | BETA | Non | +| 38 | [ICT-21b-SAECalibration-Python — que reconstruit…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-21b-SAECalibration-Python.ipynb) | BETA | Non | | 39 | [ICT-21c-SAECatastrophes-Python — forme et dynamique des…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-21c-SAECatastrophes-Python.ipynb) | BETA | Non | | 40 | [ICT-22 — LLMSubstrat : le transformer comme quatrième…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-22-LLMSubstrat-Python.ipynb) | BETA | Non | | 41 | [ICT-22b -- Moteur d'intervention causal : operer,…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-22b-CausalInterventionEngine-Python.ipynb) | BETA | Non | @@ -217,35 +218,38 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | 61 | [Geometrie des features SAE : galaxy, atome, dense --…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-41-SAE-GeometrieFeatures-Python.ipynb) | BETA | Oui | | 62 | [ICT-42 — Crosscoder : diffuser deux modèles, distilled…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-42-Crosscoder-Distillation-Python.ipynb) | BETA | Non | | 63 | [ICT-44 — La géométrie de la vérité : une direction dans…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-44-GeometryOfTruth-Python.ipynb) | BETA | Non | -| 64 | [ICT — Annexe : la contextualité du zoo de proxys est un…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Annexe-ProxyContextuality.ipynb) | BETA | Oui | -| 65 | [ICT — Substrat argumentation : trajectoires de croyance…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-BeliefTrajectories.ipynb) | BETA | Oui | -| 66 | [Argumentation strate 6 — Acceptabilité QBF :…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-QBFAcceptance.ipynb) | BETA | Oui | -| 67 | [ICT — Substrat argumentation : maintenance de la…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-TruthMaintenance.ipynb) | BETA | Oui | -| 68 | [Boucle auto-referentielle p_hat (case 2 / Epic #9533)](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-PhatSelfReference.ipynb) | BETA | Oui | -| 69 | [ICT -- Dissociation saillance / pregnance (case s ⟂ π)](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-SaillancePregnance.ipynb) | BETA | Oui | -| 70 | [ICT-Greffe4 — Le vote argumenté sur chaîne : fermer la…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Greffe4-VoteOnChain.ipynb) | BETA | Oui | -| 71 | [ICT-Life — Substrat de calibration certifié : le Jeu de…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Life-SubstratCertifie.ipynb) | BETA | Oui | -| 72 | [Tete-a-tete SAE <-> J-space -- les deux lentilles du…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-SAE-JLens-TeteATete.ipynb) | BETA | Non | -| 73 | [ICT-Synthèse — un seul appareil de mesure, cinq…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Synthese-CrossSubstrat.ipynb) | BETA | Non | +| 64 | [ICT-46 — Strate 7 : freebits de second ordre, le banc…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-46-Strate7-FreeCoordinates-Python.ipynb) | BETA | Oui | +| 65 | [ICT — Annexe : la contextualité du zoo de proxys est un…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Annexe-ProxyContextuality.ipynb) | BETA | Oui | +| 66 | [ICT — Substrat argumentation : trajectoires de croyance…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-BeliefTrajectories.ipynb) | BETA | Oui | +| 67 | [Argumentation strate 6 — Acceptabilité QBF :…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-QBFAcceptance.ipynb) | BETA | Oui | +| 68 | [ICT — Substrat argumentation : maintenance de la…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-TruthMaintenance.ipynb) | BETA | Oui | +| 69 | [Boucle auto-referentielle p_hat (case 2 / Epic #9533)](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-PhatSelfReference.ipynb) | BETA | Oui | +| 70 | [ICT -- Dissociation saillance / pregnance (case s ⟂ π)](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-SaillancePregnance.ipynb) | BETA | Oui | +| 71 | [ICT-Greffe4 — Le vote argumenté sur chaîne : fermer la…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Greffe4-VoteOnChain.ipynb) | BETA | Oui | +| 72 | [ICT-Life — Substrat de calibration certifié : le Jeu de…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Life-SubstratCertifie.ipynb) | BETA | Oui | +| 73 | [ICT-MUH — Le texte où Tegmark cite Schmidhuber :…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-MUH-FibreTegmark.ipynb) | BETA | Oui | +| 74 | [Tete-a-tete SAE <-> J-space -- les deux lentilles du…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-SAE-JLens-TeteATete.ipynb) | BETA | Non | +| 75 | [ICT-Synthèse — un seul appareil de mesure, cinq…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Synthese-CrossSubstrat.ipynb) | BETA | Non | -## Probas/Applications (3 notebooks) +## Probas/Applications (4 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| | 1 | [Percolation-Lean — le noyau fini de percolation, prouvé…](../../MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-Lean.ipynb) | BETA | Oui | | 2 | [Percolation supercritique : le géant au-dessus du seuil](../../MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-Supercritique.ipynb) | ALPHA | Oui | | 3 | [Le Framework Rational Speech Act (RSA)](../../MyIA.AI.Notebooks/Probas/Applications/Pyro_RSA_Hyperbole.ipynb) | BETA | Oui | +| 4 | [Quotients, fibres et recollement : ce qui survit à la…](../../MyIA.AI.Notebooks/Probas/Applications/Quotients-Fibres-Recollement-Python.ipynb) | BETA | Oui | ## Probas/DecisionTheory (31 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| | 1 | [Du graphe causal au do-calculus — le pont entre les…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-01-Do-Calculus.ipynb) | BETA | Oui | -| 2 | [DoWhy-1 — Exiger un estimand : l'identification causale…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-02-Dowhy-Estimand-Intervention.ipynb) | BETA | Oui | -| 3 | [DoWhy-2 — Le contrefactuel individuel : quand l'effet…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-03-Dowhy-Contrefactuel-Individuel.ipynb) | BETA | Oui | -| 4 | [DoWhy-3 — La découverte de structure : le graphe qu'on…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-04-Dowhy-Decouverte-Structure.ipynb) | BETA | Oui | -| 5 | [DoWhy-4 — Le confondeur non observé : sensibilité, pas…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-05-Dowhy-Sensibilite-Confounder.ipynb) | BETA | Oui | -| 6 | [DoWhy-5 — L'instrument faible : quand le pipeline IV…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-06-Dowhy-Instrument-Faible.ipynb) | BETA | Oui | +| 2 | [CausalBridges-02 — Exiger un estimand :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-02-Dowhy-Estimand-Intervention.ipynb) | BETA | Oui | +| 3 | [CausalBridges-03 — Le contrefactuel individuel : quand…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-03-Dowhy-Contrefactuel-Individuel.ipynb) | BETA | Oui | +| 4 | [CausalBridges-04 — La découverte de structure : le…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-04-Dowhy-Decouverte-Structure.ipynb) | BETA | Oui | +| 5 | [CausalBridges-05 — Le confondeur non observé :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-05-Dowhy-Sensibilite-Confounder.ipynb) | BETA | Oui | +| 6 | [CausalBridges-06 — L'instrument faible : quand le…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-06-Dowhy-Instrument-Faible.ipynb) | BETA | Oui | | 7 | [Méthodes quasi-expérimentales — identifier l'effet…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-07-Quasi-Experimental.ipynb) | BETA | Oui | | 8 | [Causal-Fairness — Décomposer la discrimination :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-08-Causal-Fairness.ipynb) | BETA | Oui | | 9 | [DecInfer-01-Utility-Foundations : Axiomes et Fondements](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-01-Utility-Foundations.ipynb) | BETA | Oui | @@ -266,7 +270,7 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | 24 | [DecPyMC-2-Utility-Money : Utilite de l'Argent et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-2-Utility-Money.ipynb) | BETA | Oui | | 25 | [DecPyMC-3-Multi-Attribute : Utilite Multi-Attributs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-3-Multi-Attribute.ipynb) | BETA | Oui | | 26 | [DecPyMC-4-Decision-Networks : Reseaux de Decision](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-4-Decision-Networks.ipynb) | BETA | Oui | -| 27 | [DecPyMC-5-Valeur de l'Information](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-5-Value-Information.ipynb) | BETA | Oui | +| 27 | [DecPyMC-5-Valeur de l'Information](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-5-Value-Information.ipynb) | ALPHA | Oui | | 28 | [DecPyMC-6-Systèmes Experts et Decisions Robustes](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-6-Expert-Systems.ipynb) | BETA | Oui | | 29 | [DecPyMC-7-MDPs, Bandits et POMDPs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-7-Sequential.ipynb) | BETA | Oui | | 30 | [DecPyMC-8 — Crédibilité actuarielle de Bühlmann–Straub…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-8-Actuarial-Credibility.ipynb) | BETA | Oui | @@ -276,20 +280,20 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| -| 1 | [Infer-1-Setup : Introduction et Installation](../../MyIA.AI.Notebooks/Probas/Infer/Infer-1-Setup.ipynb) | BETA | Oui | -| 2 | [Infer-10-Model-Sélection : Sélection et Comparaison de…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-10-Model-Selection.ipynb) | BETA | Oui | -| 3 | [Infer-11-Topic-Models : Latent Dirichlet Allocation…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-11-Topic-Models.ipynb) | BETA | Oui | -| 4 | [12. Modèles Hiérarchiques Bayésiens — Pooling Partiel…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-12-Modeles-Hierarchiques.ipynb) | BETA | Oui | -| 5 | [Infer-13-Crowdsourcing : Agregation de Labels et…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-13-Crowdsourcing.ipynb) | BETA | Oui | -| 6 | [Infer-14-Sequences : Hidden Markov Models et Series…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-14-Sequences.ipynb) | BETA | Oui | -| 7 | [Infer-15-Recommenders : systèmes de Recommandation](../../MyIA.AI.Notebooks/Probas/Infer/Infer-15-Recommenders.ipynb) | BETA | Oui | -| 8 | [Infer-16-Sparse-Gaussian-Process : Processus Gaussiens…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-16-Sparse-Gaussian-Process.ipynb) | BETA | Oui | -| 9 | [Infer-17 — Filtre de Kalman : systèmes dynamiques…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-17-Kalman-Filter.ipynb) | BETA | Oui | -| 10 | [Infer-18 — Détection de Rupture (Change-Point) :…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-18-Change-Point.ipynb) | BETA | Oui | -| 11 | [Infer-19 — Analyse de survie / fiabilite bayesienne :…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-19-Survival-Analysis.ipynb) | BETA | Oui | -| 12 | [Infer-1b : Introduction a Infer.NET](../../MyIA.AI.Notebooks/Probas/Infer/Infer-1b-Premiers-Modeles.ipynb) | BETA | Oui | -| 13 | [Infer-2-Gaussian-Mixtures : Distributions Gaussiennes…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-2-Gaussian-Mixtures.ipynb) | BETA | Oui | -| 14 | [Quotients, fibres et recollement : ce qui…](../../MyIA.AI.Notebooks/Probas/Applications/Quotients-Fibres-Recollement-Python.ipynb) | BETA | Oui | +| 1 | [Infer-8b-TrueSkill-Formules-Fermees : la mise a jour…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-08b-TrueSkill-Formules-Fermees-CSharp.ipynb) | BETA | Oui | +| 2 | [Infer-1-Setup : Introduction et Installation](../../MyIA.AI.Notebooks/Probas/Infer/Infer-1-Setup.ipynb) | BETA | Oui | +| 3 | [Infer-10-Model-Sélection : Sélection et Comparaison de…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-10-Model-Selection.ipynb) | BETA | Oui | +| 4 | [Infer-11-Topic-Models : Latent Dirichlet Allocation…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-11-Topic-Models.ipynb) | BETA | Oui | +| 5 | [12. Modèles Hiérarchiques Bayésiens — Pooling Partiel…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-12-Modeles-Hierarchiques.ipynb) | BETA | Oui | +| 6 | [Infer-13-Crowdsourcing : Agregation de Labels et…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-13-Crowdsourcing.ipynb) | BETA | Oui | +| 7 | [Infer-14-Sequences : Hidden Markov Models et Series…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-14-Sequences.ipynb) | BETA | Oui | +| 8 | [Infer-15-Recommenders : systèmes de Recommandation](../../MyIA.AI.Notebooks/Probas/Infer/Infer-15-Recommenders.ipynb) | BETA | Oui | +| 9 | [Infer-16-Sparse-Gaussian-Process : Processus Gaussiens…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-16-Sparse-Gaussian-Process.ipynb) | BETA | Oui | +| 10 | [Infer-17 — Filtre de Kalman : systèmes dynamiques…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-17-Kalman-Filter.ipynb) | BETA | Oui | +| 11 | [Infer-18 — Détection de Rupture (Change-Point) :…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-18-Change-Point.ipynb) | BETA | Oui | +| 12 | [Infer-19 — Analyse de survie / fiabilite bayesienne :…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-19-Survival-Analysis.ipynb) | BETA | Oui | +| 13 | [Infer-1b : Introduction a Infer.NET](../../MyIA.AI.Notebooks/Probas/Infer/Infer-1b-Premiers-Modeles.ipynb) | BETA | Oui | +| 14 | [Infer-2-Gaussian-Mixtures : Distributions Gaussiennes…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-2-Gaussian-Mixtures.ipynb) | BETA | Oui | | 15 | [Infer-2b-Debugging-Bonnes-Pratiques : Troubleshooting…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-2b-Debugging-Bonnes-Pratiques.ipynb) | BETA | Oui | | 16 | [Infer-3-Factor-Graphs : Graphes de Facteurs et…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-3-Factor-Graphs.ipynb) | BETA | Oui | | 17 | [Infer-4-Bayesian-Networks : Reseaux Bayesiens…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-4-Bayesian-Networks.ipynb) | BETA | Oui | @@ -332,7 +336,7 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | 4 | [RL-12 : Distributional RL — C51 (Categorical DQN)…](../../MyIA.AI.Notebooks/RL/rl_12_distributional_rl.ipynb) | BETA | Non | | 5 | [RL 13 - Exploration par curiosité : Random Network…](../../MyIA.AI.Notebooks/RL/rl_13_curiosity_exploration.ipynb) | BETA | Oui | | 6 | [Hierarchical RL — l'Option framework de Sutton, Precup…](../../MyIA.AI.Notebooks/RL/rl_14_hierarchical_rl.ipynb) | BETA | Oui | -| 7 | [RL-15 — GRPO (Group Relative Policy Optimization) sur…](../../MyIA.AI.Notebooks/RL/rl_15_grpo_group_relative_policy.ipynb) | ALPHA | Non | +| 7 | [RL-15 — GRPO (Group Relative Policy Optimization) sur…](../../MyIA.AI.Notebooks/RL/rl_15_grpo_group_relative_policy.ipynb) | BETA | Non | | 8 | [RL-16 : Dream-RSI — l'exploration comme code, évaluée…](../../MyIA.AI.Notebooks/RL/rl_16_dream_rsi.ipynb) | BETA | Oui | | 9 | [RL 17 - k-server et work function : la conjecture…](../../MyIA.AI.Notebooks/RL/rl_17_k_server_wfa.ipynb) | BETA | Oui | | 10 | [RL 18 - Le secrétaire matroïdal : la conjecture…](../../MyIA.AI.Notebooks/RL/rl_18_matroid_secretary.ipynb) | BETA | Oui | diff --git a/docs/curriculum/trading.md b/docs/curriculum/trading.md index 44a95449a7..e1a2a633a3 100644 --- a/docs/curriculum/trading.md +++ b/docs/curriculum/trading.md @@ -20,12 +20,12 @@ Stratégies de trading algorithmique avec QuantConnect, pipeline ML (Transformer | Métrique | Valeur | |----------|--------| -| Notebooks | 267 | +| Notebooks | 272 | | PRODUCTION | 0 | -| BETA | 248 | -| ALPHA | 19 | +| BETA | 251 | +| ALPHA | 21 | -## ML/DataScienceWithAgents (93 notebooks) +## ML/DataScienceWithAgents (98 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -42,86 +42,91 @@ Stratégies de trading algorithmique avec QuantConnect, pipeline ML (Transformer | 11 | [2.13 — Analyse d'erreurs : diagnostiquer un modèle…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.13-Analyse-Erreurs.ipynb) | BETA | Oui | | 12 | [2.14 — Explicabilité (XAI) : SHAP, LIME et…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.14-Explicabilite-SHAP-LIME-Contrefactuels.ipynb) | BETA | Oui | | 13 | [2.14b — SHAP et do-calculus : la jonction attribution…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.14b-XAI-Shap-Attribution-Causal-Bridge.ipynb) | BETA | Oui | -| 14 | [2.2 — La descente de gradient : comment un modèle…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.2-Descente-de-gradient.ipynb) | BETA | Oui | -| 15 | [2.3 — Régression linéaire et régression logistique](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3-Regression-lineaire-logistique.ipynb) | BETA | Oui | -| 16 | [Naive Bayes génératif vs régression logistique…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3b-Naive-Bayes-Generatif.ipynb) | BETA | Oui | -| 17 | [Régression en grande dimension — quand p >> n : ridge,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3c-Regression-Grande-Dimension.ipynb) | BETA | Oui | -| 18 | [Modèle gaussien, frontière LDA / QDA](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3d-Modele-Gaussien-LDA-QDA.ipynb) | BETA | Oui | -| 19 | [2.4 — Arbres de décision, forêts aléatoires et boosting](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.4-Arbres-Forets-Ensembles.ipynb) | BETA | Oui | -| 20 | [2.5 — Biais, variance, validation croisée et courbe ROC](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5-Biais-Variance-CV-ROC.ipynb) | BETA | Oui | -| 21 | [2.5b — Calibration des probabilités : reliability…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5b-Calibration-Probabilites.ipynb) | BETA | Oui | -| 22 | [2.5c — Equite par sous-groupe : compromis…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5c-Equite-Sous-Groupes.ipynb) | BETA | Oui | -| 23 | [2.6 — Clustering (KMeans) et réduction de dimension…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.6-Clustering-KMeans-PCA.ipynb) | BETA | Oui | -| 24 | [2.7 — Modèles non paramétriques : SVM et k plus proches…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.7-Modeles-Non-Parametriques.ipynb) | BETA | Oui | -| 25 | [2.7b — SMO from scratch : SVM soft-margin, boucle de…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.7b-SMO-From-Scratch.ipynb) | BETA | Oui | -| 26 | [2.7c — SVM SOTA : LIBSVM sous le capot de…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.7c-SVM-SOTA-Comparison.ipynb) | BETA | Oui | -| 27 | [2.8 — Théorie de l'apprentissage : PAC et dimension de…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8-Theorie-PAC.ipynb) | BETA | Oui | -| 28 | [2.8c — Borne + Témoin extrémal + Concentration : ce que…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8c-Borne-Temoin-Concentration.ipynb) | BETA | Oui | -| 29 | [Novikoff : la convergence du perceptron, démontrée et…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8d-Lean-Novikoff-Convergence.ipynb) | BETA | Oui | -| 30 | [2.9 — Grokking : la généralisation qui arrive en retard](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9-Grokking-Generalisation.ipynb) | BETA | Oui | -| 31 | [2.9b — GenEFT : une théorie effective de la…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9b-GenEFT-Theorie-Effective.ipynb) | BETA | Oui | -| 32 | [2.9c — Grokking : le diagramme de phases](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9c-Grokking-Diagrammes-Phases.ipynb) | BETA | Oui | -| 33 | [2.9d — Features circulaires et hélice des nombres](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9d-Features-Circulaires-Helice-Nombres.ipynb) | BETA | Non | -| 34 | [2.9e — MIPS : du réseau au programme](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9e-MIPS-Extraction-Programme.ipynb) | BETA | Non | -| 35 | [3.0 — Théorie de l'information : entropie, KL,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.0-Theorie-Information.ipynb) | BETA | Oui | -| 36 | [3.1 — La rétropropagation : la chaîne des gradients à…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.1-Retropropagation.ipynb) | BETA | Oui | -| 37 | [3.10 — Le pendant SOTA : la bibliothèque diffusers…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.10-Modeles-Generatifs-Diffusion-SOTA.ipynb) | BETA | Non | -| 38 | [3.2 — Les optimisateurs : de SGD à Adam, ce qui change…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.2-Optimisateurs.ipynb) | BETA | Oui | -| 39 | [3.3 — Régularisation : dropout, weight decay, early…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.3-Regularisation.ipynb) | BETA | Oui | -| 40 | [3.4 — Attention et Transformer from scratch : jusqu'au…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4-Attention-Transformer-From-Scratch.ipynb) | BETA | Oui | -| 41 | [3.4c — Mixture of Experts : router les jetons, croître…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4c-MoE-from-scratch.ipynb) | BETA | Non | -| 42 | [3.5 — Grokking et double descente : quand la…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.5-Phenomenes-de-Generalisation.ipynb) | BETA | Oui | -| 43 | [3.6 — Modèles génératifs : trois objectifs, trois…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6-Modeles-Generatifs.ipynb) | BETA | Oui | -| 44 | [3.6b — Modèles génératifs en PyTorch : VAE, GAN et…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6b-Modeles-Generatifs-PyTorch.ipynb) | BETA | Oui | -| 45 | [3.6d — Modèles génératifs : Score-SDE *from scratch*](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6d-Modeles-Generatifs-Score-SDE-from-scratch.ipynb) | BETA | Non | -| 46 | [3.6e — Génération conditionnelle et *classifier-free…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6e-Modeles-Generatifs-Conditionnels-from-scratch.ipynb) | BETA | Non | -| 47 | [3.7 — Distillation maître-élève : quand le savoir se…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.7-Distillation-Maitre-Eleve.ipynb) | BETA | Oui | -| 48 | [Représentations contrastives modernes — du skip-gram…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.8-Representations-Contrastives.ipynb) | BETA | Oui | -| 49 | [3.9 — Quantization FP : FP32 vers FP16 et BF16 depuis…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9-Compression-Quantization-FP.ipynb) | BETA | Oui | -| 50 | [3.9a — Compression par quantification INT8 : le réseau…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9a-Compression-Quantization-INT8.ipynb) | BETA | Non | -| 51 | [3.9b — Compression par élagage : le réseau amputé qui…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9b-Compression-Pruning-from-scratch.ipynb) | BETA | Non | -| 52 | [3.9d — Compression par distillation : transférer le…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9d-Compression-Distillation-from-scratch.ipynb) | BETA | Non | -| 53 | [3.9e — Quantification SOTA : la même INT8, par…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9e-Compression-Quantization-SOTA.ipynb) | BETA | Non | -| 54 | [3.9f — Élagage SOTA : les mêmes masques, par…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9f-Compression-Pruning-SOTA.ipynb) | BETA | Non | -| 55 | [3.9g — Comparatif compression : from scratch (Bloc A)…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9g-Compression-Comparatif-A-vs-B.ipynb) | BETA | Non | -| 56 | [4.1 — Le neurone convolutif from scratch : kernel…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.1-Conv-NumPy-Torch-Allclose.ipynb) | BETA | Oui | -| 57 | [4.2 — ConvNet profonde : pourquoi les résiduelles](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2-ConvNet-Profonde-Residuelles.ipynb) | BETA | Non | -| 58 | [Le gradient qui s'évanouit, le gradient qui survit :…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2b-Lean-GradientFlow-Vanishing.ipynb) | BETA | Oui | -| 59 | [4.2c — Détection d'objets from scratch : la grille…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2c-Detection-Anchor-From-Scratch.ipynb) | BETA | Non | -| 60 | [4.2d — Détection d'objets anchor-free : le renversement…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2d-Detection-AnchorFree-From-Scratch.ipynb) | BETA | Non | -| 61 | [4.2e — Détection d'objets from scratch : la Focal Loss](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2e-Detection-FocalLoss-From-Scratch.ipynb) | BETA | Non | -| 62 | [4.2f — Détection SOTA : fine-tuner torchvision plutôt…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2f-Detection-SOTA-Torchvision.ipynb) | BETA | Non | -| 63 | [4.2g — Détection SOTA : YOLO sous ultralytics, la…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2g-Detection-SOTA-Ultralytics.ipynb) | BETA | Non | -| 64 | [4.2h — Bench yolov5nu sur le terrain du 4.2c (chunk…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2h-YOLOv5-Bench-Ultralytics.ipynb) | BETA | Non | -| 65 | [4.2h — Détection SOTA : YOLO sous ultralytics, scènes…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2i-Detection-Ultralytics-Difficult-Scenes.ipynb) | BETA | Non | -| 66 | [4.3 — Transfer learning : réutiliser un ResNet18…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.3-TransferLearning-ResNet.ipynb) | BETA | Non | -| 67 | [WS-00a — Ondelettes 1D *from scratch* : analyse…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00a-Ondelettes-1D-from-scratch.ipynb) | BETA | Oui | -| 68 | [WS-00b — Ondelettes 2D *from scratch* : bandes…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00b-Ondelettes-2D-from-scratch.ipynb) | BETA | Oui | -| 69 | [WS-00c — Scattering 2D *from scratch* : le module rend…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00c-Scattering-from-scratch.ipynb) | BETA | Oui | -| 70 | [WS-01 — Débruitage d'images : du seuillage *from…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-01-Denoising-SOTA.ipynb) | BETA | Oui | -| 71 | [WS-02 — Scattering SOTA : kymatio contre le moteur…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-02-Scattering-SOTA.ipynb) | BETA | Non | -| 72 | [WS-03 — Synthèse : représentation construite vs…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-03-Synthese-Scattering-vs-ResNet.ipynb) | BETA | Oui | -| 73 | [Lab 1 - Les Bases de la Data Science en Python](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day1-Foundations/Labs/Lab1-PythonForDataScience.ipynb) | BETA | Oui | -| 74 | [Lab 2 - Analyser un Appel d'Offre avec l'IA](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day2-Document-Agents/Labs/Lab2-RFP-Analysis/Lab2-RFP-Analysis.ipynb) | BETA | Non | -| 75 | [Lab 3 - Pré-qualifier des Candidats avec l'IA](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day2-Document-Agents/Labs/Lab3-CV-Screening/Lab3-CV-Screening.ipynb) | BETA | Non | -| 76 | [Lab 4 - Le Nettoyage de Données avec Pandas](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab4-DataWrangling/Lab4-DataWrangling.ipynb) | BETA | Oui | -| 77 | [Lab 5 - De la Visualisation au Machine Learning](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab5-Viz-ML/Lab5-Viz-ML.ipynb) | BETA | Oui | -| 78 | [Lab 6 - Anatomie de votre premier Agent d'IA](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab6-First-Agent/Lab6-First-Agent.ipynb) | BETA | Non | -| 79 | [Lab 7 - Votre premier Agent Analyste de Données](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab7-Data-Analysis-Agent/Lab7-Data-Analysis-Agent.ipynb) | BETA | Non | -| 80 | [Lab 8: Introduction au Framework ADK et Multi-Provider](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day4-Foundations/Lab8-ADK-Introduction.ipynb) | BETA | Non | -| 81 | [Lab 9: Premier Agent ADK pour Data Science](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day4-Foundations/Lab9-First-ADK-Agent.ipynb) | BETA | Oui | -| 82 | [Lab 10: Data File Analyzer (DS-STAR Component)](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab10-File-Analyzer.ipynb) | BETA | Oui | -| 83 | [Lab 11: Planner-Coder-Verifier Loop (DS-STAR Core)](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab11-Planner-Coder-Loop.ipynb) | ALPHA | Oui | -| 84 | [Lab 12: DS-STAR Workshop - Analyse Multi-Fichiers](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12-DS-Star-Workshop.ipynb) | BETA | Oui | -| 85 | [Lab 12b : Désignation séquentielle — le contrat C4,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12b-Sequential-Orchestration.ipynb) | BETA | Non | -| 86 | [Lab 12c : Handoff entre agents — le contrat C5, le…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12c-Agent-Handoff.ipynb) | BETA | Non | -| 87 | [Lab 12d : Tracabilite de la consommation — le contrat…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12d-Token-Usage.ipynb) | BETA | Non | -| 88 | [Lab 12e: Persistance d'etat de session - une…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12e-Session-Persistence.ipynb) | BETA | Non | -| 89 | [Lab 13: Web Search pour Modèles SOTA (MLE-STAR…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab13-Web-Search-SOTA.ipynb) | BETA | Oui | -| 90 | [Lab 14: Ablation et Raffinement Ciblé (MLE-STAR…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab14-Ablation-Refinement.ipynb) | ALPHA | Oui | -| 91 | [Lab 15: Kaggle Challenge avec MLE-STAR](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab15-Kaggle-Challenge.ipynb) | BETA | Oui | -| 92 | [Lab 16: Data Science Agent avec GCP BigQuery](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day7-Production/Lab16-Data-Science-Agent.ipynb) | ALPHA | Oui | -| 93 | [Lab 17: Projet Final - Pipeline DS-STAR Complet](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day7-Production/Lab17-Final-Project.ipynb) | ALPHA | Oui | +| 14 | [2.15 — La donnée comme responsabilité : inférence…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.15-Donnee-Comme-Responsabilite-Python.ipynb) | BETA | Oui | +| 15 | [2.2 — La descente de gradient : comment un modèle…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.2-Descente-de-gradient.ipynb) | BETA | Oui | +| 16 | [2.3 — Régression linéaire et régression logistique](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3-Regression-lineaire-logistique.ipynb) | BETA | Oui | +| 17 | [Naive Bayes génératif vs régression logistique…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3b-Naive-Bayes-Generatif.ipynb) | BETA | Oui | +| 18 | [Régression en grande dimension — quand p >> n : ridge,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3c-Regression-Grande-Dimension.ipynb) | BETA | Oui | +| 19 | [Modèle gaussien, frontière LDA / QDA](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3d-Modele-Gaussien-LDA-QDA.ipynb) | BETA | Oui | +| 20 | [2.4 — Arbres de décision, forêts aléatoires et boosting](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.4-Arbres-Forets-Ensembles.ipynb) | BETA | Oui | +| 21 | [2.5 — Biais, variance, validation croisée et courbe ROC](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5-Biais-Variance-CV-ROC.ipynb) | BETA | Oui | +| 22 | [2.5b — Calibration des probabilités : reliability…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5b-Calibration-Probabilites.ipynb) | BETA | Oui | +| 23 | [2.5c — Equite par sous-groupe : compromis…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5c-Equite-Sous-Groupes.ipynb) | BETA | Oui | +| 24 | [2.5d — Dérive de distribution au déploiement :…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5d-Derive-Distribution-Deploiement.ipynb) | ALPHA | Oui | +| 25 | [2.6 — Clustering (KMeans) et réduction de dimension…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.6-Clustering-KMeans-PCA.ipynb) | BETA | Oui | +| 26 | [2.7 — Modèles non paramétriques : SVM et k plus proches…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.7-Modeles-Non-Parametriques.ipynb) | BETA | Oui | +| 27 | [2.7b — SMO from scratch : SVM soft-margin, boucle de…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.7b-SMO-From-Scratch.ipynb) | BETA | Oui | +| 28 | [2.7c — SVM SOTA : LIBSVM sous le capot de…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.7c-SVM-SOTA-Comparison.ipynb) | BETA | Oui | +| 29 | [2.8 — Théorie de l'apprentissage : PAC et dimension de…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8-Theorie-PAC.ipynb) | BETA | Oui | +| 30 | [2.8c — Borne + Témoin extrémal + Concentration : ce que…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8c-Borne-Temoin-Concentration.ipynb) | BETA | Oui | +| 31 | [Novikoff : la convergence du perceptron, démontrée et…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8d-Lean-Novikoff-Convergence.ipynb) | BETA | Oui | +| 32 | [2.9 — Grokking : la généralisation qui arrive en retard](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9-Grokking-Generalisation.ipynb) | BETA | Oui | +| 33 | [2.9b — GenEFT : une théorie effective de la…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9b-GenEFT-Theorie-Effective.ipynb) | BETA | Oui | +| 34 | [2.9c — Grokking : le diagramme de phases](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9c-Grokking-Diagrammes-Phases.ipynb) | BETA | Oui | +| 35 | [2.9d — Features circulaires et hélice des nombres](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9d-Features-Circulaires-Helice-Nombres.ipynb) | BETA | Non | +| 36 | [2.9e — MIPS : du réseau au programme](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9e-MIPS-Extraction-Programme.ipynb) | BETA | Non | +| 37 | [3.0 — Théorie de l'information : entropie, KL,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.0-Theorie-Information.ipynb) | BETA | Oui | +| 38 | [3.1 — La rétropropagation : la chaîne des gradients à…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.1-Retropropagation.ipynb) | BETA | Oui | +| 39 | [3.10 — Le pendant SOTA : la bibliothèque diffusers…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.10-Modeles-Generatifs-Diffusion-SOTA.ipynb) | BETA | Non | +| 40 | [3.11 — Le budget mémoire d'un entraînement : quatre…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.11-Budget-Memoire-Entrainement.ipynb) | BETA | Non | +| 41 | [3.12 — Les collectives : l'anneau à la main contre…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.12-Les-Collectives.ipynb) | BETA | Non | +| 42 | [3.2 — Les optimisateurs : de SGD à Adam, ce qui change…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.2-Optimisateurs.ipynb) | BETA | Oui | +| 43 | [3.3 — Régularisation : dropout, weight decay, early…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.3-Regularisation.ipynb) | BETA | Oui | +| 44 | [3.4 — Attention et Transformer from scratch : jusqu'au…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4-Attention-Transformer-From-Scratch.ipynb) | BETA | Oui | +| 45 | [3.4c — Mixture of Experts : router les jetons, croître…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4c-MoE-from-scratch.ipynb) | BETA | Non | +| 46 | [3.5 — Grokking et double descente : quand la…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.5-Phenomenes-de-Generalisation.ipynb) | BETA | Oui | +| 47 | [3.6 — Modèles génératifs : trois objectifs, trois…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6-Modeles-Generatifs.ipynb) | BETA | Oui | +| 48 | [3.6b — Modèles génératifs en PyTorch : VAE, GAN et…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6b-Modeles-Generatifs-PyTorch.ipynb) | BETA | Oui | +| 49 | [3.6d — Modèles génératifs : Score-SDE *from scratch*](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6d-Modeles-Generatifs-Score-SDE-from-scratch.ipynb) | BETA | Non | +| 50 | [3.6e — Génération conditionnelle et *classifier-free…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6e-Modeles-Generatifs-Conditionnels-from-scratch.ipynb) | BETA | Non | +| 51 | [3.7 — Distillation maître-élève : quand le savoir se…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.7-Distillation-Maitre-Eleve.ipynb) | BETA | Oui | +| 52 | [Représentations contrastives modernes — du skip-gram…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.8-Representations-Contrastives.ipynb) | BETA | Oui | +| 53 | [3.9 — Quantization FP : FP32 vers FP16 et BF16 depuis…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9-Compression-Quantization-FP.ipynb) | BETA | Oui | +| 54 | [3.9a — Compression par quantification INT8 : le réseau…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9a-Compression-Quantization-INT8.ipynb) | BETA | Non | +| 55 | [3.9b — Compression par élagage : le réseau amputé qui…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9b-Compression-Pruning-from-scratch.ipynb) | BETA | Non | +| 56 | [3.9d — Compression par distillation : transférer le…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9d-Compression-Distillation-from-scratch.ipynb) | BETA | Non | +| 57 | [3.9e — Quantification SOTA : la même INT8, par…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9e-Compression-Quantization-SOTA.ipynb) | BETA | Non | +| 58 | [3.9f — Élagage SOTA : les mêmes masques, par…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9f-Compression-Pruning-SOTA.ipynb) | BETA | Non | +| 59 | [3.9g — Comparatif compression : from scratch (Bloc A)…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9g-Compression-Comparatif-A-vs-B.ipynb) | BETA | Non | +| 60 | [4.1 — Le neurone convolutif from scratch : kernel…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.1-Conv-NumPy-Torch-Allclose.ipynb) | BETA | Oui | +| 61 | [4.2 — ConvNet profonde : pourquoi les résiduelles](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2-ConvNet-Profonde-Residuelles.ipynb) | BETA | Non | +| 62 | [Le gradient qui s'évanouit, le gradient qui survit :…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2b-Lean-GradientFlow-Vanishing.ipynb) | BETA | Oui | +| 63 | [4.2c — Détection d'objets from scratch : la grille…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2c-Detection-Anchor-From-Scratch.ipynb) | BETA | Non | +| 64 | [4.2d — Détection d'objets anchor-free : le renversement…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2d-Detection-AnchorFree-From-Scratch.ipynb) | BETA | Non | +| 65 | [4.2e — Détection d'objets from scratch : la Focal Loss](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2e-Detection-FocalLoss-From-Scratch.ipynb) | BETA | Non | +| 66 | [4.2f — Détection SOTA : fine-tuner torchvision plutôt…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2f-Detection-SOTA-Torchvision.ipynb) | BETA | Non | +| 67 | [4.2g — Détection SOTA : YOLO sous ultralytics, la…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2g-Detection-SOTA-Ultralytics.ipynb) | BETA | Non | +| 68 | [4.2h — Bench yolov5nu sur le terrain du 4.2c (chunk…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2h-YOLOv5-Bench-Ultralytics.ipynb) | BETA | Non | +| 69 | [4.2h — Détection SOTA : YOLO sous ultralytics, scènes…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2i-Detection-Ultralytics-Difficult-Scenes.ipynb) | BETA | Non | +| 70 | [4.2j — Détection SOTA : un second wrapper, LibreYOLO,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2j-Detection-SOTA-LibreYOLO.ipynb) | BETA | Non | +| 71 | [4.3 — Transfer learning : réutiliser un ResNet18…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.3-TransferLearning-ResNet.ipynb) | BETA | Non | +| 72 | [WS-00a — Ondelettes 1D *from scratch* : analyse…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00a-Ondelettes-1D-from-scratch.ipynb) | BETA | Oui | +| 73 | [WS-00b — Ondelettes 2D *from scratch* : bandes…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00b-Ondelettes-2D-from-scratch.ipynb) | BETA | Oui | +| 74 | [WS-00c — Scattering 2D *from scratch* : le module rend…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00c-Scattering-from-scratch.ipynb) | BETA | Oui | +| 75 | [WS-01 — Débruitage d'images : du seuillage *from…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-01-Denoising-SOTA.ipynb) | BETA | Oui | +| 76 | [WS-02 — Scattering SOTA : kymatio contre le moteur…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-02-Scattering-SOTA.ipynb) | BETA | Non | +| 77 | [WS-03 — Synthèse : représentation construite vs…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-03-Synthese-Scattering-vs-ResNet.ipynb) | BETA | Oui | +| 78 | [Lab 1 - Les Bases de la Data Science en Python](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day1-Foundations/Labs/Lab1-PythonForDataScience.ipynb) | BETA | Oui | +| 79 | [Lab 2 - Analyser un Appel d'Offre avec l'IA](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day2-Document-Agents/Labs/Lab2-RFP-Analysis/Lab2-RFP-Analysis.ipynb) | BETA | Non | +| 80 | [Lab 3 - Pré-qualifier des Candidats avec l'IA](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day2-Document-Agents/Labs/Lab3-CV-Screening/Lab3-CV-Screening.ipynb) | BETA | Non | +| 81 | [Lab 4 - Le Nettoyage de Données avec Pandas](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab4-DataWrangling/Lab4-DataWrangling.ipynb) | BETA | Oui | +| 82 | [Lab 5 - De la Visualisation au Machine Learning](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab5-Viz-ML/Lab5-Viz-ML.ipynb) | BETA | Oui | +| 83 | [Lab 6 - Anatomie de votre premier Agent d'IA](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab6-First-Agent/Lab6-First-Agent.ipynb) | BETA | Non | +| 84 | [Lab 7 - Votre premier Agent Analyste de Données](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track1-LangChain/Day3-Data-Agents/Labs/Lab7-Data-Analysis-Agent/Lab7-Data-Analysis-Agent.ipynb) | BETA | Non | +| 85 | [Lab 8: Introduction au Framework ADK et Multi-Provider](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day4-Foundations/Lab8-ADK-Introduction.ipynb) | BETA | Non | +| 86 | [Lab 9: Premier Agent ADK pour Data Science](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day4-Foundations/Lab9-First-ADK-Agent.ipynb) | BETA | Oui | +| 87 | [Lab 10: Data File Analyzer (DS-STAR Component)](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab10-File-Analyzer.ipynb) | BETA | Oui | +| 88 | [Lab 11: Planner-Coder-Verifier Loop (DS-STAR Core)](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab11-Planner-Coder-Loop.ipynb) | ALPHA | Oui | +| 89 | [Lab 12: DS-STAR Workshop - Analyse Multi-Fichiers](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12-DS-Star-Workshop.ipynb) | BETA | Oui | +| 90 | [Lab 12b : Désignation séquentielle — le contrat C4,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12b-Sequential-Orchestration.ipynb) | BETA | Non | +| 91 | [Lab 12c : Handoff entre agents — le contrat C5, le…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12c-Agent-Handoff.ipynb) | BETA | Non | +| 92 | [Lab 12d : Tracabilite de la consommation — le contrat…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12d-Token-Usage.ipynb) | BETA | Non | +| 93 | [Lab 12e: Persistance d'etat de session - une…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12e-Session-Persistence.ipynb) | BETA | Non | +| 94 | [Lab 13: Web Search pour Modèles SOTA (MLE-STAR…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab13-Web-Search-SOTA.ipynb) | BETA | Oui | +| 95 | [Lab 14: Ablation et Raffinement Ciblé (MLE-STAR…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab14-Ablation-Refinement.ipynb) | ALPHA | Oui | +| 96 | [Lab 15: Kaggle Challenge avec MLE-STAR](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab15-Kaggle-Challenge.ipynb) | BETA | Oui | +| 97 | [Lab 16: Data Science Agent avec GCP BigQuery](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day7-Production/Lab16-Data-Science-Agent.ipynb) | ALPHA | Oui | +| 98 | [Lab 17: Projet Final - Pipeline DS-STAR Complet](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day7-Production/Lab17-Final-Project.ipynb) | ALPHA | Oui | ## ML/ML.Net (23 notebooks) @@ -151,24 +156,25 @@ Stratégies de trading algorithmique avec QuantConnect, pipeline ML (Transformer | 22 | [ML-9 : Detection d'anomalies avec Randomized PCA](../../MyIA.AI.Notebooks/ML/ML.Net/ML-9-Anomaly-Detection.ipynb) | BETA | Oui | | 23 | [TP : Prevision des ventes d'assurance](../../MyIA.AI.Notebooks/ML/ML.Net/TP-prevision-ventes.ipynb) | BETA | Oui | -## Probas/Applications (3 notebooks) +## Probas/Applications (4 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| | 1 | [Percolation-Lean — le noyau fini de percolation, prouvé…](../../MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-Lean.ipynb) | BETA | Oui | | 2 | [Percolation supercritique : le géant au-dessus du seuil](../../MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-Supercritique.ipynb) | ALPHA | Oui | | 3 | [Le Framework Rational Speech Act (RSA)](../../MyIA.AI.Notebooks/Probas/Applications/Pyro_RSA_Hyperbole.ipynb) | BETA | Oui | +| 4 | [Quotients, fibres et recollement : ce qui survit à la…](../../MyIA.AI.Notebooks/Probas/Applications/Quotients-Fibres-Recollement-Python.ipynb) | BETA | Oui | ## Probas/DecisionTheory (31 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| | 1 | [Du graphe causal au do-calculus — le pont entre les…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-01-Do-Calculus.ipynb) | BETA | Oui | -| 2 | [DoWhy-1 — Exiger un estimand : l'identification causale…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-02-Dowhy-Estimand-Intervention.ipynb) | BETA | Oui | -| 3 | [DoWhy-2 — Le contrefactuel individuel : quand l'effet…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-03-Dowhy-Contrefactuel-Individuel.ipynb) | BETA | Oui | -| 4 | [DoWhy-3 — La découverte de structure : le graphe qu'on…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-04-Dowhy-Decouverte-Structure.ipynb) | BETA | Oui | -| 5 | [DoWhy-4 — Le confondeur non observé : sensibilité, pas…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-05-Dowhy-Sensibilite-Confounder.ipynb) | BETA | Oui | -| 6 | [DoWhy-5 — L'instrument faible : quand le pipeline IV…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-06-Dowhy-Instrument-Faible.ipynb) | BETA | Oui | +| 2 | [CausalBridges-02 — Exiger un estimand :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-02-Dowhy-Estimand-Intervention.ipynb) | BETA | Oui | +| 3 | [CausalBridges-03 — Le contrefactuel individuel : quand…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-03-Dowhy-Contrefactuel-Individuel.ipynb) | BETA | Oui | +| 4 | [CausalBridges-04 — La découverte de structure : le…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-04-Dowhy-Decouverte-Structure.ipynb) | BETA | Oui | +| 5 | [CausalBridges-05 — Le confondeur non observé :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-05-Dowhy-Sensibilite-Confounder.ipynb) | BETA | Oui | +| 6 | [CausalBridges-06 — L'instrument faible : quand le…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-06-Dowhy-Instrument-Faible.ipynb) | BETA | Oui | | 7 | [Méthodes quasi-expérimentales — identifier l'effet…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-07-Quasi-Experimental.ipynb) | BETA | Oui | | 8 | [Causal-Fairness — Décomposer la discrimination :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-08-Causal-Fairness.ipynb) | BETA | Oui | | 9 | [DecInfer-01-Utility-Foundations : Axiomes et Fondements](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-01-Utility-Foundations.ipynb) | BETA | Oui | @@ -189,7 +195,7 @@ Stratégies de trading algorithmique avec QuantConnect, pipeline ML (Transformer | 24 | [DecPyMC-2-Utility-Money : Utilite de l'Argent et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-2-Utility-Money.ipynb) | BETA | Oui | | 25 | [DecPyMC-3-Multi-Attribute : Utilite Multi-Attributs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-3-Multi-Attribute.ipynb) | BETA | Oui | | 26 | [DecPyMC-4-Decision-Networks : Reseaux de Decision](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-4-Decision-Networks.ipynb) | BETA | Oui | -| 27 | [DecPyMC-5-Valeur de l'Information](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-5-Value-Information.ipynb) | BETA | Oui | +| 27 | [DecPyMC-5-Valeur de l'Information](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-5-Value-Information.ipynb) | ALPHA | Oui | | 28 | [DecPyMC-6-Systèmes Experts et Decisions Robustes](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-6-Expert-Systems.ipynb) | BETA | Oui | | 29 | [DecPyMC-7-MDPs, Bandits et POMDPs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-7-Sequential.ipynb) | BETA | Oui | | 30 | [DecPyMC-8 — Crédibilité actuarielle de Bühlmann–Straub…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-8-Actuarial-Credibility.ipynb) | BETA | Oui | @@ -199,20 +205,20 @@ Stratégies de trading algorithmique avec QuantConnect, pipeline ML (Transformer | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| -| 1 | [Infer-1-Setup : Introduction et Installation](../../MyIA.AI.Notebooks/Probas/Infer/Infer-1-Setup.ipynb) | BETA | Oui | -| 2 | [Infer-10-Model-Sélection : Sélection et Comparaison de…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-10-Model-Selection.ipynb) | BETA | Oui | -| 3 | [Infer-11-Topic-Models : Latent Dirichlet Allocation…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-11-Topic-Models.ipynb) | BETA | Oui | -| 4 | [12. Modèles Hiérarchiques Bayésiens — Pooling Partiel…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-12-Modeles-Hierarchiques.ipynb) | BETA | Oui | -| 5 | [Infer-13-Crowdsourcing : Agregation de Labels et…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-13-Crowdsourcing.ipynb) | BETA | Oui | -| 6 | [Infer-14-Sequences : Hidden Markov Models et Series…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-14-Sequences.ipynb) | BETA | Oui | -| 7 | [Infer-15-Recommenders : systèmes de Recommandation](../../MyIA.AI.Notebooks/Probas/Infer/Infer-15-Recommenders.ipynb) | BETA | Oui | -| 8 | [Infer-16-Sparse-Gaussian-Process : Processus Gaussiens…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-16-Sparse-Gaussian-Process.ipynb) | BETA | Oui | -| 9 | [Infer-17 — Filtre de Kalman : systèmes dynamiques…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-17-Kalman-Filter.ipynb) | BETA | Oui | -| 10 | [Infer-18 — Détection de Rupture (Change-Point) :…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-18-Change-Point.ipynb) | BETA | Oui | -| 11 | [Infer-19 — Analyse de survie / fiabilite bayesienne :…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-19-Survival-Analysis.ipynb) | BETA | Oui | -| 12 | [Infer-1b : Introduction a Infer.NET](../../MyIA.AI.Notebooks/Probas/Infer/Infer-1b-Premiers-Modeles.ipynb) | BETA | Oui | -| 13 | [Infer-2-Gaussian-Mixtures : Distributions Gaussiennes…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-2-Gaussian-Mixtures.ipynb) | BETA | Oui | -| 14 | [Quotients, fibres et recollement : ce qui…](../../MyIA.AI.Notebooks/Probas/Applications/Quotients-Fibres-Recollement-Python.ipynb) | BETA | Oui | +| 1 | [Infer-8b-TrueSkill-Formules-Fermees : la mise a jour…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-08b-TrueSkill-Formules-Fermees-CSharp.ipynb) | BETA | Oui | +| 2 | [Infer-1-Setup : Introduction et Installation](../../MyIA.AI.Notebooks/Probas/Infer/Infer-1-Setup.ipynb) | BETA | Oui | +| 3 | [Infer-10-Model-Sélection : Sélection et Comparaison de…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-10-Model-Selection.ipynb) | BETA | Oui | +| 4 | [Infer-11-Topic-Models : Latent Dirichlet Allocation…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-11-Topic-Models.ipynb) | BETA | Oui | +| 5 | [12. Modèles Hiérarchiques Bayésiens — Pooling Partiel…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-12-Modeles-Hierarchiques.ipynb) | BETA | Oui | +| 6 | [Infer-13-Crowdsourcing : Agregation de Labels et…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-13-Crowdsourcing.ipynb) | BETA | Oui | +| 7 | [Infer-14-Sequences : Hidden Markov Models et Series…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-14-Sequences.ipynb) | BETA | Oui | +| 8 | [Infer-15-Recommenders : systèmes de Recommandation](../../MyIA.AI.Notebooks/Probas/Infer/Infer-15-Recommenders.ipynb) | BETA | Oui | +| 9 | [Infer-16-Sparse-Gaussian-Process : Processus Gaussiens…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-16-Sparse-Gaussian-Process.ipynb) | BETA | Oui | +| 10 | [Infer-17 — Filtre de Kalman : systèmes dynamiques…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-17-Kalman-Filter.ipynb) | BETA | Oui | +| 11 | [Infer-18 — Détection de Rupture (Change-Point) :…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-18-Change-Point.ipynb) | BETA | Oui | +| 12 | [Infer-19 — Analyse de survie / fiabilite bayesienne :…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-19-Survival-Analysis.ipynb) | BETA | Oui | +| 13 | [Infer-1b : Introduction a Infer.NET](../../MyIA.AI.Notebooks/Probas/Infer/Infer-1b-Premiers-Modeles.ipynb) | BETA | Oui | +| 14 | [Infer-2-Gaussian-Mixtures : Distributions Gaussiennes…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-2-Gaussian-Mixtures.ipynb) | BETA | Oui | | 15 | [Infer-2b-Debugging-Bonnes-Pratiques : Troubleshooting…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-2b-Debugging-Bonnes-Pratiques.ipynb) | BETA | Oui | | 16 | [Infer-3-Factor-Graphs : Graphes de Facteurs et…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-3-Factor-Graphs.ipynb) | BETA | Oui | | 17 | [Infer-4-Bayesian-Networks : Reseaux Bayesiens…](../../MyIA.AI.Notebooks/Probas/Infer/Infer-4-Bayesian-Networks.ipynb) | BETA | Oui | @@ -251,38 +257,37 @@ Stratégies de trading algorithmique avec QuantConnect, pipeline ML (Transformer |---|----------|----------|------------| | 1 | [M16 — HAR asymétrique débiaisé : le signal survit-il…](../../MyIA.AI.Notebooks/QuantConnect/ML-Training-Pipeline/m3_har_asymmetric_semivariance.ipynb) | BETA | Non | -## QuantConnect/Python (28 notebooks) +## QuantConnect/Python (27 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| | 1 | [QC-Py-01 : Configuration et Premier Backtest…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-01-Setup.ipynb) | BETA | Non | | 2 | [Objectifs d'Apprentissage](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-04-Research-Workflow.ipynb) | BETA | Non | | 3 | [QC-Py-05b - F-Score de Piotroski : l'article, le…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-05b-FScore-Piotroski.ipynb) | BETA | Non | -| 4 | [QC-Py-12b - Validité du backtest et signification…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-12b-Backtest-Validity.ipynb) | BETA | Non | -| 5 | [QC-Py-14b - Liquidité et coûts d'exécution : ce que le…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-14b-Liquidity-Execution-Costs.ipynb) | BETA | Non | -| 6 | [QC-Py-18 - Feature Engineering pour Machine Learning…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-18-ML-Features-Engineering.ipynb) | ALPHA | Non | -| 7 | [Objectifs d'Apprentissage](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-19-ML-Supervised-Classification.ipynb) | BETA | Non | -| 8 | [QC-Py-23b - PatchTST et iTransformer pour Prevision…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-23b-PatchTST-iTransformer.ipynb) | BETA | Non | -| 9 | [QC-Py-23c — Modèles de fondation pour séries…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-23c-TimesFM-Foundation-Models.ipynb) | BETA | Non | -| 10 | [QC-Py-28b - Macro et régimes : du cycle économique au…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-28b-Macro-Cycle-Regimes.ipynb) | ALPHA | Non | -| 11 | [QC-Py-29 - Valorisation d'un dérivé : trois moteurs, un…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-29-Derivatives-Valuation.ipynb) | BETA | Non | -| 12 | [QC-Py-30 - LSTM Training Multi-Asset (GPU)](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-30-LSTM-Training.ipynb) | BETA | Non | -| 13 | [QC-Py-31 - Transformer Encoder Multi-Asset (GPU)](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-31-Transformer-Training.ipynb) | BETA | Non | -| 14 | [QC-Py-32 - Reinforcement Learning DQN pour le Trading](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-32-RL-DQN-Trading.ipynb) | BETA | Non | -| 15 | [QC-Py-33 - Reinforcement Learning PPO pour le Trading](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-33-RL-PPO-Trading.ipynb) | BETA | Non | -| 16 | [QC-Py-34 - SAC et A2C : Comparaison d'Agents RL pour le…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-34-RL-SAC-A2C-Trading.ipynb) | BETA | Non | -| 17 | [QC-Py-35 - Reinforcement Learning pour la Construction…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-35-RL-Portfolio-Construction.ipynb) | ALPHA | Non | -| 18 | [QC-Py-40 : Paper Trading Binance - Mean Reversion…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-40-PaperTrading-Binance.ipynb) | BETA | Non | -| 19 | [QC-Py-41 : Paper Trading IBKR - SP500 Momentum](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-41-PaperTrading-IBKR.ipynb) | BETA | Non | -| 20 | [QC-Py-Cloud-01 : Analyse de Sentiment FinBERT sur QC…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-01-FinBERT-Sentiment.ipynb) | ALPHA | Non | -| 21 | [QC-Py-Cloud-02 : Classification de Texte et Sentiment…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-02-ML-Classification.ipynb) | ALPHA | Non | -| 22 | [QC-Py-Cloud-03 : Parite de Risque (Risk Parity)](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-03-Risk-Parity.ipynb) | BETA | Non | -| 23 | [QC-Py-Cloud-05 : Prevision par Reseau de Neurones (MLP)](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-05-MLP-Forecasting.ipynb) | ALPHA | Non | -| 24 | [Value Factor Z-Score — Sélection multi-facteurs…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-08-ValueFactor-ZScore.ipynb) | BETA | Non | -| 25 | [Option Wheel — Le paradoxe du win-rate eleve](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-09-OptionWheel.ipynb) | BETA | Non | -| 26 | [QC-Py-Cloud-10 : Reinforcement Learning - DQN Trading](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-10-RL-DQN-Trading.ipynb) | ALPHA | Non | -| 27 | [QC-Py-Cloud-14 — Dual Momentum : Asset Sélection…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-14-DualMomentum.ipynb) | BETA | Non | -| 28 | [Workflow : Téléchargement et gestion des datasets](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Dataset-Workflow.ipynb) | ALPHA | Non | +| 4 | [QC-Py-14b - Liquidité et coûts d'exécution : ce que le…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-14b-Liquidity-Execution-Costs.ipynb) | BETA | Non | +| 5 | [QC-Py-18 - Feature Engineering pour Machine Learning…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-18-ML-Features-Engineering.ipynb) | ALPHA | Non | +| 6 | [Objectifs d'Apprentissage](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-19-ML-Supervised-Classification.ipynb) | BETA | Non | +| 7 | [QC-Py-23b - PatchTST et iTransformer pour Prevision…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-23b-PatchTST-iTransformer.ipynb) | BETA | Non | +| 8 | [QC-Py-23c — Modèles de fondation pour séries…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-23c-TimesFM-Foundation-Models.ipynb) | BETA | Non | +| 9 | [QC-Py-28b - Macro et régimes : du cycle économique au…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-28b-Macro-Cycle-Regimes.ipynb) | ALPHA | Non | +| 10 | [QC-Py-29 - Valorisation d'un dérivé : trois moteurs, un…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-29-Derivatives-Valuation.ipynb) | BETA | Non | +| 11 | [QC-Py-30 - LSTM Training Multi-Asset (GPU)](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-30-LSTM-Training.ipynb) | BETA | Non | +| 12 | [QC-Py-31 - Transformer Encoder Multi-Asset (GPU)](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-31-Transformer-Training.ipynb) | BETA | Non | +| 13 | [QC-Py-32 - Reinforcement Learning DQN pour le Trading](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-32-RL-DQN-Trading.ipynb) | BETA | Non | +| 14 | [QC-Py-33 - Reinforcement Learning PPO pour le Trading](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-33-RL-PPO-Trading.ipynb) | BETA | Non | +| 15 | [QC-Py-34 - SAC et A2C : Comparaison d'Agents RL pour le…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-34-RL-SAC-A2C-Trading.ipynb) | BETA | Non | +| 16 | [QC-Py-35 - Reinforcement Learning pour la Construction…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-35-RL-Portfolio-Construction.ipynb) | ALPHA | Non | +| 17 | [QC-Py-40 : Paper Trading Binance - Mean Reversion…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-40-PaperTrading-Binance.ipynb) | BETA | Non | +| 18 | [QC-Py-41 : Paper Trading IBKR - SP500 Momentum](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-41-PaperTrading-IBKR.ipynb) | BETA | Non | +| 19 | [QC-Py-Cloud-01 : Analyse de Sentiment FinBERT sur QC…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-01-FinBERT-Sentiment.ipynb) | ALPHA | Non | +| 20 | [QC-Py-Cloud-02 : Classification de Texte et Sentiment…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-02-ML-Classification.ipynb) | ALPHA | Non | +| 21 | [QC-Py-Cloud-03 : Parite de Risque (Risk Parity)](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-03-Risk-Parity.ipynb) | BETA | Non | +| 22 | [QC-Py-Cloud-05 : Prevision par Reseau de Neurones (MLP)](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-05-MLP-Forecasting.ipynb) | ALPHA | Non | +| 23 | [Value Factor Z-Score — Sélection multi-facteurs…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-08-ValueFactor-ZScore.ipynb) | BETA | Non | +| 24 | [Option Wheel — Le paradoxe du win-rate eleve](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-09-OptionWheel.ipynb) | BETA | Non | +| 25 | [QC-Py-Cloud-10 : Reinforcement Learning - DQN Trading](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-10-RL-DQN-Trading.ipynb) | ALPHA | Non | +| 26 | [QC-Py-Cloud-14 — Dual Momentum : Asset Sélection…](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-14-DualMomentum.ipynb) | BETA | Non | +| 27 | [Workflow : Téléchargement et gestion des datasets](../../MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Dataset-Workflow.ipynb) | ALPHA | Non | ## QuantConnect/kelly_lean (2 notebooks)