diff --git a/COURSE_CATALOG.generated.json b/COURSE_CATALOG.generated.json index 9d37eaa5f4..e58f07a733 100644 --- a/COURSE_CATALOG.generated.json +++ b/COURSE_CATALOG.generated.json @@ -22,8 +22,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "37d9bb504", - "executed_at": "2026-10-01T16:16:39+02:00", + "last_success_sha": "7de698405", + "executed_at": "2026-10-09T09:04:12+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -39,19 +39,19 @@ "creation": { "class": "HEAVY", "history": "COMPLETE", - "revisions": 20, - "authors": 2, + "revisions": 21, + "authors": 3, "first_commit": "2026-05-10", - "span_days": 144 + "span_days": 152 } }, "owner_logique": "", - "last_validation": "2026-10-01", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#18421, #18429", - "cells_total": 45, + "last_validation": "2026-10-09", + "last_validator": "jsboige+myia-po-2023@gmail.com", + "issue_pr_associee": "#17040, #19928", + "cells_total": 44, "cells_code": 16, - "cells_markdown": 29, + "cells_markdown": 28, "cells_with_outputs": 12, "cells_without_outputs": 0, "requires_api": false, @@ -83,8 +83,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "387461d6b", - "executed_at": "2026-09-23T02:58:54+02:00", + "last_success_sha": "7de698405", + "executed_at": "2026-10-09T09:04:12+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -100,19 +100,19 @@ "creation": { "class": "HEAVY", "history": "COMPLETE", - "revisions": 13, - "authors": 2, + "revisions": 14, + "authors": 3, "first_commit": "2026-05-10", - "span_days": 136 + "span_days": 152 } }, "owner_logique": "", - "last_validation": "2026-09-23", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17083, #17312", - "cells_total": 37, + "last_validation": "2026-10-09", + "last_validator": "jsboige+myia-po-2023@gmail.com", + "issue_pr_associee": "#17040, #19928", + "cells_total": 35, "cells_code": 15, - "cells_markdown": 22, + "cells_markdown": 20, "cells_with_outputs": 11, "cells_without_outputs": 0, "requires_api": false, @@ -571,15 +571,15 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "6aa8452e7", - "executed_at": "2026-10-02T12:22:16+02:00", + "last_success_sha": "23bc52d03", + "executed_at": "2026-10-09T14:08:44+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { "schema": 1, "execution": { "class": "LIGHT", - "wall_seconds": 2.8, + "wall_seconds": 10.3, "cells_timed": 10, "cells_code": 10, "coverage": "FULL", @@ -588,16 +588,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 5, + "revisions": 6, "authors": 1, "first_commit": "2026-09-25", - "span_days": 7 + "span_days": 14 } }, "owner_logique": "", - "last_validation": "2026-10-02", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #18649", + "issue_pr_associee": "#19930, #19941", "cells_total": 24, "cells_code": 10, "cells_markdown": 14, @@ -998,8 +998,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "8410ab71a", - "executed_at": "2026-10-08T12:40:53+02:00", + "last_success_sha": "fdc9748b7", + "executed_at": "2026-10-09T15:46:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -1015,16 +1015,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 4, + "revisions": 5, "authors": 1, "first_commit": "2026-10-02", - "span_days": 6 + "span_days": 7 } }, "owner_logique": "", - "last_validation": "2026-10-08", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17151, #19781", + "issue_pr_associee": "#19711, #19771", "cells_total": 28, "cells_code": 12, "cells_markdown": 16, @@ -1036,6 +1036,67 @@ "requires_wsl": false, "executable_locally": true }, + { + "path": "Complexity/Complexity-06-Simuler-Circuit-Quantique-Classiquement-Python.ipynb", + "title": "Complexity-06 — Simuler un circuit quantique classiquement", + "serie": "Complexity", + "sous_serie": "", + "kernel": "Python 3", + "status": "READY", + "pedagogical_role": "", + "maturity": "BETA", + "editorial": "BETA", + "reproducibility": "EXECUTED", + "scientific_review": "UNASSESSED", + "scientific_review_stale": false, + "scientific_review_detail": { + "grade": "UNASSESSED", + "stale": false, + "code_sha": "a945cea4d85e4b2d45c73ae564c86bc57b75dc476fdba8b95803ab0642319d6a", + "reviewed_code_sha": "", + "reviewed_by": "", + "peer": false, + "sorry_free": false + }, + "production_signed": false, + "last_success_sha": "fdc9748b7", + "executed_at": "2026-10-09T15:46:16+02:00", + "forensic_category": "A_ALL_EXEC_OK", + "duree_estimee": "15min", + "resource_cost": { + "schema": 1, + "execution": { + "class": "LIGHT", + "wall_seconds": 0.3, + "cells_timed": 4, + "cells_code": 4, + "coverage": "FULL", + "external": [] + }, + "creation": { + "class": "LIGHT", + "history": "COMPLETE", + "revisions": 1, + "authors": 1, + "first_commit": "2026-10-09", + "span_days": 0 + } + }, + "owner_logique": "", + "last_validation": "2026-10-09", + "last_validator": "jsboige@gmail.com", + "issue_pr_associee": "#19711, #19771", + "cells_total": 13, + "cells_code": 4, + "cells_markdown": 9, + "cells_with_outputs": 3, + "cells_without_outputs": 0, + "requires_api": false, + "requires_gpu": false, + "requires_cloud": false, + "requires_wsl": false, + "executable_locally": true + }, { "path": "Complexity/Complexity-06b-AaronsonGottesman-Dequantification-Python.ipynb", "title": "Complexity-06b — Déquantifier les suprématies (Aaronson–Gottesman)", @@ -1046,28 +1107,28 @@ "pedagogical_role": "", "maturity": "BETA", "editorial": "BETA", - "reproducibility": "REPRODUCED", + "reproducibility": "EXECUTED", "scientific_review": "UNASSESSED", "scientific_review_stale": false, "scientific_review_detail": { "grade": "UNASSESSED", "stale": false, - "code_sha": "64f89b1ecc3fe72b35dfb8792441fcc81092e4061c9a23279e3efdf43648a1db", + "code_sha": "fe27dd0c2feb21186c2559a9f3d7e6364097f60a69468ca0c09acb1faa6660d0", "reviewed_code_sha": "", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - "last_success_sha": "651519dde", - "executed_at": "2026-10-08T13:23:28+02:00", + "last_success_sha": "57f4c84c2", + "executed_at": "2026-10-11T00:51:40+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { "schema": 1, "execution": { "class": "LIGHT", - "wall_seconds": 19.6, + "wall_seconds": 33.7, "cells_timed": 14, "cells_code": 14, "coverage": "FULL", @@ -1076,16 +1137,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 3, + "revisions": 6, "authors": 1, "first_commit": "2026-10-07", - 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"last_validation": "2026-10-02", + "last_validation": "2026-10-10", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#18694", + "issue_pr_associee": "#14442, #20029", "cells_total": 36, "cells_code": 14, "cells_markdown": 22, @@ -1427,8 +1488,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "e83a16367", + "executed_at": "2026-10-09T10:51:37+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -1444,16 +1505,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 5, + "revisions": 6, "authors": 2, "first_commit": "2026-08-23", - "span_days": 38 + "span_days": 47 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#14442, #20026", "cells_total": 34, "cells_code": 14, "cells_markdown": 20, @@ -1488,8 +1549,8 @@ "sorry_free": false }, "production_signed": false, - 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"issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#14442, #20029", "cells_total": 40, "cells_code": 13, "cells_markdown": 27, @@ -1856,8 +1917,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "75f73b2e6", + "executed_at": "2026-10-09T08:52:10+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -1875,16 +1936,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#14442, #20023", "cells_total": 33, "cells_code": 13, "cells_markdown": 20, @@ -1980,8 +2041,8 @@ "sorry_free": false }, "production_signed": false, - 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"revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#14442, #20026", "cells_total": 23, "cells_code": 9, "cells_markdown": 14, @@ -2104,8 +2165,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "e83a16367", + "executed_at": "2026-10-09T10:51:37+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -2121,16 +2182,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#14442, #20026", "cells_total": 64, "cells_code": 25, "cells_markdown": 39, @@ -2226,8 +2287,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "7d654af1f", - "executed_at": "2026-10-02T00:29:26+02:00", + "last_success_sha": "6f87c167b", + "executed_at": "2026-10-10T04:35:12+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -2241,18 +2302,18 @@ "external": [] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 2, + "revisions": 3, "authors": 1, "first_commit": "2026-09-30", - "span_days": 2 + "span_days": 10 } }, "owner_logique": "po-2024", - "last_validation": "2026-10-02", + "last_validation": "2026-10-10", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#18694", + "issue_pr_associee": "#14442, #20029", "cells_total": 38, "cells_code": 17, "cells_markdown": 21, @@ -2411,8 +2472,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "6f87c167b", + "executed_at": "2026-10-10T04:35:12+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -2428,16 +2489,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 10 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-10", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#14442, #20029", "cells_total": 25, "cells_code": 10, "cells_markdown": 15, @@ -2718,8 +2779,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "7d654af1f", - "executed_at": "2026-10-02T00:29:26+02:00", + "last_success_sha": "6f87c167b", + "executed_at": "2026-10-10T04:35:12+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -2733,18 +2794,18 @@ "external": [] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 2, + "revisions": 3, "authors": 1, "first_commit": "2026-09-30", - "span_days": 2 + "span_days": 10 } }, "owner_logique": "po-2024", - "last_validation": "2026-10-02", + "last_validation": "2026-10-10", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#18694", + "issue_pr_associee": "#14442, #20029", "cells_total": 38, "cells_code": 15, "cells_markdown": 23, @@ -2903,8 +2964,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "4e1a16038", - "executed_at": "2026-10-03T08:22:36+02:00", + "last_success_sha": "61f54301c", + "executed_at": "2026-10-09T17:27:48+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -2918,18 +2979,18 @@ "external": [] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 2, + "revisions": 3, "authors": 1, "first_commit": "2026-09-30", - "span_days": 3 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-10-03", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#18774", + "issue_pr_associee": "#14442, #20030", "cells_total": 45, "cells_code": 16, "cells_markdown": 29, @@ -2964,8 +3025,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "cd3d8e7bd", + "executed_at": "2026-10-09T04:43:39+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -2981,16 +3042,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#17040, #19842, #19947", "cells_total": 63, "cells_code": 23, "cells_markdown": 40, @@ -3025,8 +3086,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "d4f61774e", - "executed_at": "2026-10-02T04:22:03+02:00", + "last_success_sha": "75f73b2e6", + "executed_at": "2026-10-09T08:52:10+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -3044,16 +3105,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 3, + "revisions": 4, "authors": 1, "first_commit": "2026-09-30", - "span_days": 2 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-10-02", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#4362, #18678", + "issue_pr_associee": "#14442, #20023", "cells_total": 30, "cells_code": 11, "cells_markdown": 19, @@ -3210,8 +3271,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "e83a16367", + "executed_at": "2026-10-09T10:51:37+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -3227,16 +3288,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#14442, #20026", "cells_total": 37, "cells_code": 14, "cells_markdown": 23, @@ -3332,8 +3393,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "75f73b2e6", + "executed_at": "2026-10-09T08:52:10+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -3351,16 +3412,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#14442, #20023", "cells_total": 31, "cells_code": 12, "cells_markdown": 19, @@ -3395,8 +3456,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "75f73b2e6", + "executed_at": "2026-10-09T08:52:10+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -3412,16 +3473,16 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 6, + "revisions": 7, "authors": 2, "first_commit": "2026-09-11", - "span_days": 19 + "span_days": 28 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#14442, #20023", "cells_total": 34, "cells_code": 11, "cells_markdown": 23, @@ -3639,8 +3700,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "75f73b2e6", + "executed_at": "2026-10-09T08:52:10+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -3656,16 +3717,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#14442, #20023", "cells_total": 24, "cells_code": 11, "cells_markdown": 13, @@ -3700,8 +3761,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "4e1a16038", - "executed_at": "2026-10-03T08:22:36+02:00", + "last_success_sha": "61f54301c", + "executed_at": "2026-10-09T17:27:48+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -3715,18 +3776,18 @@ "external": [] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 2, + "revisions": 3, "authors": 1, "first_commit": "2026-09-30", - "span_days": 3 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-10-03", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#18774", + "issue_pr_associee": "#14442, #20030", "cells_total": 32, "cells_code": 11, "cells_markdown": 21, @@ -3822,8 +3883,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "78cd444f0", - "executed_at": "2026-10-02T08:13:56+02:00", + "last_success_sha": "61f54301c", + "executed_at": "2026-10-09T17:27:48+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -3837,18 +3898,18 @@ "external": [] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 2, + "revisions": 3, "authors": 1, "first_commit": "2026-09-30", - "span_days": 2 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-10-02", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#17107, #18711", + "issue_pr_associee": "#14442, #20030", "cells_total": 32, "cells_code": 11, "cells_markdown": 21, @@ -4129,8 +4190,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "cd3d8e7bd", + "executed_at": "2026-10-09T04:43:39+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -4148,16 +4209,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#17040, #19842, #19947", "cells_total": 23, "cells_code": 10, "cells_markdown": 13, @@ -4192,8 +4253,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "61f54301c", + "executed_at": "2026-10-09T17:27:48+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4209,16 +4270,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#14442, #20030", "cells_total": 26, "cells_code": 11, "cells_markdown": 15, @@ -4436,8 +4497,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "61f54301c", + "executed_at": "2026-10-09T17:27:48+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4451,21 +4512,21 @@ "external": [] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 1, + "revisions": 3, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", - "cells_total": 40, + "issue_pr_associee": "#14442, #20030", + "cells_total": 39, "cells_code": 14, - "cells_markdown": 26, + "cells_markdown": 25, "cells_with_outputs": 14, "cells_without_outputs": 0, "requires_api": false, @@ -4558,8 +4619,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "61f54301c", + "executed_at": "2026-10-09T17:27:48+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4575,16 +4636,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#14442, #20030", "cells_total": 34, "cells_code": 13, "cells_markdown": 21, @@ -4619,8 +4680,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "cd3d8e7bd", + "executed_at": "2026-10-09T04:43:39+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4636,19 +4697,19 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", - "cells_total": 48, + "issue_pr_associee": "#17040, #19842, #19947", + "cells_total": 47, "cells_code": 15, - "cells_markdown": 33, + "cells_markdown": 32, "cells_with_outputs": 4, "cells_without_outputs": 0, "requires_api": false, @@ -4680,8 +4741,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "75f73b2e6", + "executed_at": "2026-10-09T08:52:10+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4697,18 +4758,18 @@ ] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 1, + "revisions": 3, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", + "issue_pr_associee": "#14442, #20023", "cells_total": 43, "cells_code": 19, "cells_markdown": 24, @@ -4743,8 +4804,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "61f54301c", + "executed_at": "2026-10-09T17:27:48+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4758,21 +4819,21 @@ "external": [] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 1, + "revisions": 3, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", - "cells_total": 30, + "issue_pr_associee": "#14442, #20030", + "cells_total": 27, "cells_code": 10, - "cells_markdown": 20, + "cells_markdown": 17, "cells_with_outputs": 10, "cells_without_outputs": 0, "requires_api": false, @@ -4865,8 +4926,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "4e1a16038", - "executed_at": "2026-10-03T08:22:36+02:00", + "last_success_sha": "5a192d007", + "executed_at": "2026-10-09T17:28:16+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -4880,18 +4941,18 @@ "external": [] }, "creation": { - "class": "LIGHT", + "class": "MODERATE", "history": "COMPLETE", - "revisions": 2, + "revisions": 3, "authors": 1, "first_commit": "2026-09-30", - "span_days": 3 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-10-03", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#18774", + "issue_pr_associee": "#14442, #20032", "cells_total": 30, "cells_code": 11, "cells_markdown": 19, @@ -4926,8 +4987,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "fd180cddd", + "executed_at": "2026-10-09T04:44:13+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "1h", "resource_cost": { @@ -4945,19 +5006,19 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - "span_days": 0 + "span_days": 9 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-30", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #14944, #18001", - "cells_total": 66, + "issue_pr_associee": "#17040, #19842, #19948", + "cells_total": 64, "cells_code": 26, - "cells_markdown": 40, + "cells_markdown": 38, "cells_with_outputs": 17, "cells_without_outputs": 0, "requires_api": false, @@ -4989,8 +5050,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "09e96fa5e", - "executed_at": "2026-09-30T00:39:31+02:00", + "last_success_sha": "75f73b2e6", + "executed_at": "2026-10-09T08:52:10+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -5006,16 +5067,16 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-09-30", - 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"title": "ICT-23 — PersonaCatastrophe : la fronce de Thom appliquee au desalignement emergent", + "title": "ICT-23 — PersonaCatastrophe : la fronce de Thom appliquée au désalignement émergentCapstone strate 5 — Epic #4588 / #5104 (Partie 1 CPU-only).Ce notebook est le micro-analogue des phénomènes Anthropic(*Natural Émergent Misalignment from Reward Hacking in Production RL* — inoculation prompting, novembre 2025, [arXiv:2511.18397](https://arxiv.org/abs/2511.18397))et OpenAI (*Persona Features*, juin 2025, [arXiv:2506.19823](https://arxiv.org/abs/2506.19823))traduit dans le langage de la théorie des catastrophes de Rene Thom(1972). Le substrat est un agent (un LLM) dont l'identite p(appelee *persona*) est un paramètre d'ordre soumis a deux contrôlesanthropiques :* facteur de division b = pression de récompense r. C'est la variable qu'on balaie : un sous-systeme d'entrainement peut *recompenser* le comportement b -> +inf (récompense la persona émergente) ou b -> -inf (récompense l'identité alignee).* facteur normal a = -(transgression cumulee) * (charge sémantique). C'est negatif quand la transgression ponderee par l'interdit subjectif (la \"charge sémantique\" du tabou) depasse un seuil ; positif sinon (inoculation explicite, permission forte, ou charge s -> 0).Le potentiel reste celui de Thom, inchange depuis ICT-10", "serie": "IIT", "sous_serie": "ICT-Series", "kernel": "Python 3", @@ -27506,44 +27941,44 @@ "scientific_review_detail": { "grade": "RESEARCH", "stale": true, - "code_sha": "e30beb1843d2a899db86ddc2b63afe02f15bd89c9390b54b7eaca49a5a87414c", + "code_sha": "dd388731322c2130ba8fa229027e6aba14bc93c1f5af7da28bf2a4c311e869bb", "reviewed_code_sha": "3f8486094a815e35a0125779eccf46f747d9085f9a693d138cf868686e7d613b", "reviewed_by": "", "peer": false, "sorry_free": false }, "production_signed": false, - "last_success_sha": "25d168bc9", - "executed_at": "2026-10-06T16:47:46+02:00", + "last_success_sha": "80f5ecb30", + "executed_at": "2026-10-11T00:32:55+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { 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"first_commit": "2026-05-23", - "span_days": 117 + "span_days": 139 } }, "owner_logique": "po-2024", - "last_validation": "2026-09-17", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#15719, #15795", + "last_validation": "2026-10-09", + "last_validator": "jsboige+myia-po-2023@gmail.com", + "issue_pr_associee": "#17793, #19912", "cells_total": 44, "cells_code": 15, "cells_markdown": 29, @@ -83691,8 +85606,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "a3c5742cd", - "executed_at": "2026-10-07T17:23:31+02:00", + "last_success_sha": "c7e371f67", + "executed_at": "2026-10-09T09:57:33+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "resource_cost": { @@ -83708,19 +85623,19 @@ "creation": { "class": "LIGHT", "history": "COMPLETE", - "revisions": 1, + "revisions": 2, "authors": 1, "first_commit": "2026-10-07", - "span_days": 0 + "span_days": 2 } }, "owner_logique": "po-2024", - "last_validation": "2026-10-07", + "last_validation": "2026-10-09", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #19502", - "cells_total": 39, + "issue_pr_associee": "#17040, #19902", + "cells_total": 38, "cells_code": 13, - "cells_markdown": 26, + "cells_markdown": 25, "cells_with_outputs": 10, "cells_without_outputs": 0, "requires_api": false, @@ -84063,8 +85978,8 @@ "sorry_free": false }, "production_signed": false, - "last_success_sha": "a3c5742cd", - "executed_at": "2026-10-07T17:23:31+02:00", + "last_success_sha": "2d68d5e6a", + "executed_at": "2026-10-11T00:37:56+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "resource_cost": { @@ -84080,19 +85995,19 @@ "creation": { "class": "MODERATE", "history": "COMPLETE", - "revisions": 4, + "revisions": 5, "authors": 1, "first_commit": "2026-09-15", - "span_days": 22 + "span_days": 26 } }, "owner_logique": "po-2024", - "last_validation": "2026-10-07", + "last_validation": "2026-10-11", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#16231, #19502", - "cells_total": 30, + "issue_pr_associee": "#13410, #20278", + "cells_total": 31, "cells_code": 15, - "cells_markdown": 15, + "cells_markdown": 16, "cells_with_outputs": 14, "cells_without_outputs": 0, "requires_api": false, diff --git a/COURSE_CATALOG.generated.md b/COURSE_CATALOG.generated.md index b6f1b3f079..6bd4812247 100644 --- a/COURSE_CATALOG.generated.md +++ b/COURSE_CATALOG.generated.md @@ -5,28 +5,29 @@ # CoursIA Notebook Catalog -Total notebooks: 1376 +Total notebooks: 1407 ## Status Summary - **BROKEN**: 2 -- **DEMO**: 212 -- **READY**: 1162 -- **TOTAL**: 1376 +- **DEMO**: 215 +- **READY**: 1190 +- **TOTAL**: 1407 ## Maturity Summary -- **ALPHA**: 72 -- **BETA**: 1207 -- **DRAFT**: 93 +- **ALPHA**: 74 +- **BETA**: 1227 +- **DRAFT**: 102 - **TEMPLATE**: 4 -- **TOTAL**: 1376 +- **TOTAL**: 1407 ## Series / Sub-series Totals | Series | Sub-series | Notebooks | |--------|-----------|-----------| | GenAI | 00-GenAI-Environment | 7 | +| GenAI | 3D | 2 | | GenAI | Audio | 38 | | GenAI | CaseStudies | 5 | | GenAI | FallacyDetection | 5 | @@ -46,45 +47,45 @@ Total notebooks: 1376 | Search | Part2-CSP | 18 | | Search | Part4-Metaheuristics | 35 | | Search | Part5-Frontieres | 10 | -| ML | DataScienceWithAgents | 108 | +| ML | DataScienceWithAgents | 114 | | ML | ML.Net | 23 | | SymbolicAI | Racine | 1 | | SymbolicAI | Argument_Analysis | 32 | -| SymbolicAI | Lean | 89 | +| SymbolicAI | Lean | 96 | | SymbolicAI | Planners | 25 | | SymbolicAI | SemanticWeb | 28 | -| SymbolicAI | SmartContracts | 31 | +| SymbolicAI | SmartContracts | 32 | | SymbolicAI | SMT | 47 | | SymbolicAI | SymbolicLearning | 27 | | SymbolicAI | Tweety | 39 | | QuantConnect | kelly_lean | 6 | | QuantConnect | ML-Training-Pipeline | 4 | | QuantConnect | projects | 49 | -| QuantConnect | Python | 61 | -| GameTheory | Racine | 99 | -| GameTheory | SocialChoice | 11 | +| QuantConnect | Python | 62 | +| GameTheory | Racine | 101 | +| GameTheory | SocialChoice | 12 | | Sudoku | Racine | 38 | | Probas | Racine | 1 | -| Probas | Applications | 4 | -| Probas | DecisionTheory | 32 | +| Probas | Applications | 8 | +| Probas | DecisionTheory | 33 | | Probas | Infer | 21 | | Probas | PyMC | 20 | | IIT | Racine | 6 | -| IIT | ICT-Series | 88 | +| IIT | ICT-Series | 93 | | RL | Racine | 24 | | RL | PostTraining | 11 | | CaseStudies | Diagnostic-Medical | 2 | | CaseStudies | Oncology-Planning | 2 | | CaseStudies | SmartGrid-Energy | 2 | -| Complexity | Racine | 13 | +| Complexity | Racine | 14 | | Compression | Racine | 1 | | NLP | Racine | 5 | | cross-series | socle-metadata-driven | 2 | -| **TOTAL** | | **1376** | +| **TOTAL** | | **1407** | ## By Series -### GenAI (267 notebooks) — BROKEN:2, DEMO:127, READY:138 | ALPHA:23, BETA:223, DRAFT:18, TEMPLATE:3 +### GenAI (269 notebooks) — BROKEN:2, DEMO:129, READY:138 | ALPHA:23, BETA:224, DRAFT:19, TEMPLATE:3 #### 00-GenAI-Environment (7) @@ -98,6 +99,13 @@ Total notebooks: 1376 | 6 | [00-6-Local-Docker-Deployment.ipynb](MyIA.AI.Notebooks/GenAI/00-GenAI-Environment/00-6-Local-Docker-Deployment.ipynb) | Deploiement Docker Local des Services GenAI | Python 3 | DEMO | BETA | 45min | po-2025 | | 7 | [00-7-Terminal-Long-Runs.ipynb](MyIA.AI.Notebooks/GenAI/00-GenAI-Environment/00-7-Terminal-Long-Runs.ipynb) | GenAI Environment — Terminal pour les longs… | Python 3 | DEMO | BETA | 45min | po-2025 | +#### 3D (2) + +| # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | +|---|----------|-------|--------|--------|----------|----------|-------| +| 1 | [3D-01-NeRF-From-Scratch.ipynb](MyIA.AI.Notebooks/GenAI/3D/3D-01-NeRF-From-Scratch.ipynb) | 3D-01 — NeRF from scratch : représenter une scène… | Python 3 | DEMO | ALPHA | 1h | po-2025 | +| 2 | [3D-02-NeRF-Critic.ipynb](MyIA.AI.Notebooks/GenAI/3D/3D-02-NeRF-Critic.ipynb) | 3D-02 — Critique de NeRF : cinq limitations… | Python 3 | DEMO | DRAFT | 45min | po-2025 | + #### Audio (38) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | @@ -221,7 +229,7 @@ Total notebooks: 1376 | 7 | [07-Aspire-SemanticFleet-MultiConnector.ipynb](MyIA.AI.Notebooks/GenAI/Integrations-DotNet/Aspire/07-Aspire-SemanticFleet-MultiConnector.ipynb) | Aspire : le routeur MultiConnector — vetting en… | .NET (C#) | READY | BETA | 45min | po-2025 | | 8 | [08-Aspire-AsyncFFI-Dotnet.ipynb](MyIA.AI.Notebooks/GenAI/Integrations-DotNet/Aspire/08-Aspire-AsyncFFI-Dotnet.ipynb) | Aspire : l'asynchrone aux frontieres natives -… | .NET (C#) | READY | BETA | 30min | po-2025 | | 9 | [09-Aspire-Harness-CopilotSdk.ipynb](MyIA.AI.Notebooks/GenAI/Integrations-DotNet/Aspire/09-Aspire-Harness-CopilotSdk.ipynb) | Aspire : le harness Copilot SDK — CopilotClient,… | .NET (C#) | READY | BETA | 45min | po-2025 | -| 10 | [01-GitHub-Copilot-SDK-Binding.ipynb](MyIA.AI.Notebooks/GenAI/Integrations-DotNet/CopilotSDK/01-GitHub-Copilot-SDK-Binding.ipynb) | GitHub Copilot SDK en C# : binding, streaming,… | .NET (C#) | READY | ALPHA | 30min | po-2025 | +| 10 | [01-GitHub-Copilot-SDK-Binding.ipynb](MyIA.AI.Notebooks/GenAI/Integrations-DotNet/CopilotSDK/01-GitHub-Copilot-SDK-Binding.ipynb) | GitHub Copilot SDK en C# : binding, streaming,… | .NET (C#) | READY | BETA | 45min | po-2025 | | 11 | [01-EFCore-Requetes-Compilees.ipynb](MyIA.AI.Notebooks/GenAI/Integrations-DotNet/EFCore/01-EFCore-Requetes-Compilees.ipynb) | EF Core : des requêtes vérifiées à la compilation | .NET (C#) | READY | BETA | 30min | po-2025 | | 12 | [01-Orleans-Grains-Agents.ipynb](MyIA.AI.Notebooks/GenAI/Integrations-DotNet/Orleans/01-Orleans-Grains-Agents.ipynb) | Orleans : des acteurs stateful pour les workloads… | .NET (C#) | READY | DRAFT | 30min | po-2025 | | 13 | [02-Orleans-Aspire-CoHost.ipynb](MyIA.AI.Notebooks/GenAI/Integrations-DotNet/Orleans/02-Orleans-Aspire-CoHost.ipynb) | Orleans × Aspire : le silo orchestré, les… | .NET (C#) | READY | BETA | 45min | po-2025 | @@ -612,150 +620,156 @@ Total notebooks: 1376 | 9 | [Frontieres-09-RCPSP-Max-Feasibility-Bounds-Python.ipynb](MyIA.AI.Notebooks/Search/Part5-Frontieres/Frontieres-09-RCPSP-Max-Feasibility-Bounds-Python.ipynb) | Frontieres-09 — RCPSP/max : quand la faisabilité… | Python 3 | READY | BETA | 45min | po-2025 | | 10 | [Frontieres-10-NeuralDiving-Coloration-Python.ipynb](MyIA.AI.Notebooks/Search/Part5-Frontieres/Frontieres-10-NeuralDiving-Coloration-Python.ipynb) | Frontieres-10 — Neural diving : un plongeur appris… | Python 3 | READY | BETA | 30min | po-2025 | -### ML (131 notebooks) — DEMO:21, READY:110 | ALPHA:8, BETA:117, DRAFT:6 +### ML (137 notebooks) — DEMO:21, READY:116 | ALPHA:8, BETA:123, DRAFT:6 -#### DataScienceWithAgents (108) +#### DataScienceWithAgents (114) | # | 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 | 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 | -| 7 | [2.11c-Lasso-SOTA-Comparison.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11c-Lasso-SOTA-Comparison.ipynb) | 2.11c — Lasso SOTA : coordinate descent, LassoCV,… | Python 3 | READY | ALPHA | 30min | po-2023 | -| 8 | [2.11d-Optimisation-ADMM-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11d-Optimisation-ADMM-From-Scratch.ipynb) | 2.11d — ADMM from scratch | Python 3 | READY | ALPHA | 30min | po-2023 | -| 9 | [2.11e-CVXPY-Optimisation.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11e-CVXPY-Optimisation.ipynb) | 2.11e — CVXPY : le problème déclaré, le solveur… | Python 3 | READY | DRAFT | 30min | po-2023 | -| 10 | [2.11f-Comparaison-Optimisation-Convexe.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11f-Comparaison-Optimisation-Convexe.ipynb) | 2.11f — Comparaison bloc A / bloc B : le tableau… | Python 3 | READY | BETA | 30min | po-2023 | -| 11 | [2.12-Donnees-Desequilibrees.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.12-Donnees-Desequilibrees.ipynb) | 2.12 — Données déséquilibrées : la courbe PR, les… | Python 3 | READY | BETA | 30min | po-2023 | -| 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 | [2.15-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 | [2.4b-AdaBoost-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.4b-AdaBoost-From-Scratch.ipynb) | 2.4b — AdaBoost *from scratch* : booster des… | Python 3 | READY | BETA | 45min | po-2023 | -| 23 | [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 | -| 24 | [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 | -| 25 | [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 | -| 26 | [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 | -| 27 | [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 | -| 28 | [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 | -| 29 | [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 | -| 30 | [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 | -| 31 | [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 | -| 32 | [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 | -| 33 | [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 | -| 34 | [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 | -| 35 | [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 | -| 36 | [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 | -| 37 | [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 | -| 38 | [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 | -| 39 | [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 | -| 40 | [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 | -| 41 | [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 | -| 42 | [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 | -| 43 | [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 | -| 44 | [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 | -| 45 | [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 | -| 46 | [3.13b-Deux-Cartes-Reelles-DDP-FSDP-nccl.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.13b-Deux-Cartes-Reelles-DDP-FSDP-nccl.ipynb) | 3.13b — Deux vraies cartes : DDP et FSDP sous… | Python 3 | DEMO | DRAFT | 30min | po-2023 | -| 47 | [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 | -| 48 | [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 | -| 49 | [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 | -| 50 | [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 | -| 51 | [3.4d-Fourier-Features-Biais-Spectral-Python.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4d-Fourier-Features-Biais-Spectral-Python.ipynb) | 3.4d — Fourier features et biais spectral : quand… | Python 3 | READY | ALPHA | 30min | po-2023 | -| 52 | [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 | -| 53 | [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 | -| 54 | [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 | -| 55 | [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 | -| 56 | [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 | 1h30 | po-2023 | -| 57 | [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 | -| 58 | [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 | -| 59 | [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 | -| 60 | [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 | -| 61 | [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 | -| 62 | [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 | -| 63 | [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 | -| 64 | [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 | -| 65 | [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 | -| 66 | [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 | -| 67 | [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 | -| 68 | [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 | -| 69 | [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 | -| 70 | [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 | -| 71 | [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 | -| 72 | [4.4-Detection-Anchor-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.4-Detection-Anchor-From-Scratch.ipynb) | 4.4 — Détection d'objets from scratch : la grille… | Python 3 | DEMO | BETA | 45min | po-2023 | -| 73 | [4.4b-Detection-AnchorFree-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.4b-Detection-AnchorFree-From-Scratch.ipynb) | 4.4b — Détection d'objets anchor-free : le… | coursia-ml-training | READY | BETA | 45min | po-2023 | -| 74 | [4.4c-Detection-FocalLoss-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.4c-Detection-FocalLoss-From-Scratch.ipynb) | 4.4c — Détection d'objets from scratch : la Focal… | Python 3 | READY | BETA | 30min | po-2023 | -| 75 | [4.5-Detection-SOTA-Torchvision.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5-Detection-SOTA-Torchvision.ipynb) | 4.5 — Détection SOTA : fine-tuner torchvision… | Python 3 | DEMO | BETA | 45min | po-2023 | -| 76 | [4.5b-Detection-SOTA-Ultralytics.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5b-Detection-SOTA-Ultralytics.ipynb) | 4.5b — Détection SOTA : YOLO sous ultralytics, la… | Python 3 | DEMO | BETA | 45min | po-2023 | -| 77 | [4.5c-YOLOv5-Bench-Ultralytics.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5c-YOLOv5-Bench-Ultralytics.ipynb) | 4.5c — Bench yolov5nu sur le terrain du 4.4 (chunk… | Python (coursia-ml-training) | READY | BETA | 30min | po-2023 | -| 78 | [4.5d-Detection-SOTA-LibreYOLO.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5d-Detection-SOTA-LibreYOLO.ipynb) | 4.5d — Détection SOTA : un second wrapper,… | Python 3 | READY | BETA | 45min | po-2023 | -| 79 | [4.6-Detection-Ultralytics-Difficult-Scenes.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.6-Detection-Ultralytics-Difficult-Scenes.ipynb) | 4.5c — Détection SOTA : YOLO sous ultralytics,… | Python 3 (ipykernel) | DEMO | BETA | 45min | po-2023 | -| 80 | [4.6b-Detection-Adversarial-Camouflage.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.6b-Detection-Adversarial-Camouflage.ipynb) | 4.6b — Détection SOTA : le renversement — le… | Python 3 (ipykernel) | DEMO | BETA | 45min | po-2023 | -| 81 | [4.6c-Detection-Dazzle-Garment-StyleTransfer.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.6c-Detection-Dazzle-Garment-StyleTransfer.ipynb) | 4.6c — Du patch collé au vêtement porté : le… | Py310-Gpu | DEMO | BETA | 1h | po-2023 | -| 82 | [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 | -| 83 | [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 | -| 84 | [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 | -| 85 | [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 | -| 86 | [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 | -| 87 | [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 | -| 88 | [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 | -| 89 | [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 | -| 90 | [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 | -| 91 | [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 | -| 92 | [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 | -| 93 | [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 | -| 94 | [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 | -| 95 | [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 | -| 96 | [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 | -| 97 | [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 | -| 98 | [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 | -| 99 | [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 | -| 100 | [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 | -| 101 | [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 | -| 102 | [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 | -| 103 | [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 | -| 104 | [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 | -| 105 | [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 | -| 106 | [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 | -| 107 | [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 | -| 108 | [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 | +| 1 | [1.1-Python_pour_la_Data_Science.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.1-Python_pour_la_Data_Science.ipynb) | 1.1 - Python pour la Data Science | Python 3 | READY | BETA | 45min | po-2023 | +| 2 | [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 | +| 3 | [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 | +| 4 | [1.4-Visualisation_Matplotlib_Seaborn.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.4-Visualisation_Matplotlib_Seaborn.ipynb) | 1.4 - Visualisation : Matplotlib puis Seaborn | Python 3 | READY | BETA | 45min | po-2023 | +| 5 | [1.5-Exploration_Nettoyage_Donnees_Reelles.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.5-Exploration_Nettoyage_Donnees_Reelles.ipynb) | 1.5 - Exploration et nettoyage de données réelles | Python 3 | READY | BETA | 45min | po-2023 | +| 6 | [1.6-Statistiques_Descriptives.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.6-Statistiques_Descriptives.ipynb) | 1.6 - Statistiques descriptives | Python 3 | READY | BETA | 30min | po-2023 | +| 7 | [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 | +| 8 | [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 | +| 9 | [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 | +| 10 | [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 | +| 11 | [2.11c-Lasso-SOTA-Comparison.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11c-Lasso-SOTA-Comparison.ipynb) | 2.11c — Lasso SOTA : coordinate descent, LassoCV,… | Python 3 | READY | ALPHA | 30min | po-2023 | +| 12 | [2.11d-Optimisation-ADMM-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11d-Optimisation-ADMM-From-Scratch.ipynb) | 2.11d — ADMM from scratch | Python 3 | READY | ALPHA | 30min | po-2023 | +| 13 | [2.11e-CVXPY-Optimisation.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11e-CVXPY-Optimisation.ipynb) | 2.11e — CVXPY : le problème déclaré, le solveur… | Python 3 | READY | DRAFT | 30min | po-2023 | +| 14 | [2.11f-Comparaison-Optimisation-Convexe.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11f-Comparaison-Optimisation-Convexe.ipynb) | 2.11f — Comparaison bloc A / bloc B : le tableau… | Python 3 | READY | BETA | 30min | po-2023 | +| 15 | [2.12-Donnees-Desequilibrees.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.12-Donnees-Desequilibrees.ipynb) | 2.12 — Données déséquilibrées : la courbe PR, les… | Python 3 | READY | BETA | 30min | po-2023 | +| 16 | [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 | +| 17 | [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 | +| 18 | [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 | +| 19 | [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 | +| 20 | [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 | +| 21 | [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 | +| 22 | [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 | +| 23 | [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 | +| 24 | [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 | +| 25 | [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 | +| 26 | [2.4b-AdaBoost-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.4b-AdaBoost-From-Scratch.ipynb) | 2.4b — AdaBoost *from scratch* : booster des… | Python 3 | READY | BETA | 45min | po-2023 | +| 27 | [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 | +| 28 | [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 | +| 29 | [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 | +| 30 | [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 | +| 31 | [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 | +| 32 | [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 | +| 33 | [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 | +| 34 | [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 | +| 35 | [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 | +| 36 | [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 | +| 37 | [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 | +| 38 | [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 | +| 39 | [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 | +| 40 | [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 | +| 41 | [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 | +| 42 | [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 | +| 43 | [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 | +| 44 | [2.9f-Grokking-Theorie-Effective-Lean.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9f-Grokking-Theorie-Effective-Lean.ipynb) | 2.9f - Théorie effective du grokking en Lean :… | Lean 4 (WSL) | READY | BETA | 30min | po-2023 | +| 45 | [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 | +| 46 | [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 | +| 47 | [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 | +| 48 | [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 | +| 49 | [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 | +| 50 | [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 | +| 51 | [3.13b-Deux-Cartes-Reelles-DDP-FSDP-nccl.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.13b-Deux-Cartes-Reelles-DDP-FSDP-nccl.ipynb) | 3.13b — Deux vraies cartes : DDP et FSDP sous… | Python 3 | DEMO | DRAFT | 30min | po-2023 | +| 52 | [3.14-Debug-Entrainement-N-Apprend-Pas-Python.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.14-Debug-Entrainement-N-Apprend-Pas-Python.ipynb) | 3.14 - Debogage d un entrainement qui tourne mais… | Python 3 | READY | BETA | 30min | po-2023 | +| 53 | [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 | +| 54 | [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 | +| 55 | [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 | +| 56 | [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 | +| 57 | [3.4d-Fourier-Features-Biais-Spectral-Python.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4d-Fourier-Features-Biais-Spectral-Python.ipynb) | 3.4d — Fourier features et biais spectral : quand… | Python 3 | READY | ALPHA | 30min | po-2023 | +| 58 | [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 | +| 59 | [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 | +| 60 | [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 | +| 61 | [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 | +| 62 | [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 | 1h30 | po-2023 | +| 63 | [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 | +| 64 | [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 | +| 65 | [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 | +| 66 | [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 | +| 67 | [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 | +| 68 | [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 | +| 69 | [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 | +| 70 | [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 | +| 71 | [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 | +| 72 | [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 | +| 73 | [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 | +| 74 | [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 | +| 75 | [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 | +| 76 | [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 | +| 77 | [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 | +| 78 | [4.4-Detection-Anchor-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.4-Detection-Anchor-From-Scratch.ipynb) | 4.4 — Détection d'objets from scratch : la grille… | Python 3 | DEMO | BETA | 45min | po-2023 | +| 79 | [4.4b-Detection-AnchorFree-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.4b-Detection-AnchorFree-From-Scratch.ipynb) | 4.4b — Détection d'objets anchor-free : le… | coursia-ml-training | READY | BETA | 45min | po-2023 | +| 80 | [4.4c-Detection-FocalLoss-From-Scratch.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.4c-Detection-FocalLoss-From-Scratch.ipynb) | 4.4c — Détection d'objets from scratch : la Focal… | Python 3 | READY | BETA | 30min | po-2023 | +| 81 | [4.5-Detection-SOTA-Torchvision.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5-Detection-SOTA-Torchvision.ipynb) | 4.5 — Détection SOTA : fine-tuner torchvision… | Python 3 | DEMO | BETA | 45min | po-2023 | +| 82 | [4.5b-Detection-SOTA-Ultralytics.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5b-Detection-SOTA-Ultralytics.ipynb) | 4.5b — Détection SOTA : YOLO sous ultralytics, la… | Python 3 | DEMO | BETA | 45min | po-2023 | +| 83 | [4.5c-YOLOv5-Bench-Ultralytics.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5c-YOLOv5-Bench-Ultralytics.ipynb) | 4.5c — Bench yolov5nu sur le terrain du 4.4 (chunk… | Python (coursia-ml-training) | READY | BETA | 30min | po-2023 | +| 84 | [4.5d-Detection-SOTA-LibreYOLO.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5d-Detection-SOTA-LibreYOLO.ipynb) | 4.5d — Détection SOTA : un second wrapper,… | Python 3 | READY | BETA | 45min | po-2023 | +| 85 | [4.6-Detection-Ultralytics-Difficult-Scenes.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.6-Detection-Ultralytics-Difficult-Scenes.ipynb) | 4.5c — Détection SOTA : YOLO sous ultralytics,… | Python 3 (ipykernel) | DEMO | BETA | 45min | po-2023 | +| 86 | [4.6b-Detection-Adversarial-Camouflage.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.6b-Detection-Adversarial-Camouflage.ipynb) | 4.6b — Détection SOTA : le renversement — le… | Python 3 (ipykernel) | DEMO | BETA | 45min | po-2023 | +| 87 | [4.6c-Detection-Dazzle-Garment-StyleTransfer.ipynb](MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.6c-Detection-Dazzle-Garment-StyleTransfer.ipynb) | 4.6c — Du patch collé au vêtement porté : le… | Py310-Gpu | DEMO | BETA | 1h | po-2023 | +| 88 | [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 | +| 89 | [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 | +| 90 | [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 | +| 91 | [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 | +| 92 | [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 | +| 93 | [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 | +| 94 | [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 | +| 95 | [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 | +| 96 | [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 | +| 97 | [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 | +| 98 | [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 | +| 99 | [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 | +| 100 | [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 | +| 101 | [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 | +| 102 | [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 | +| 103 | [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 | +| 104 | [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 | +| 105 | [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 | +| 106 | [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 | +| 107 | [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 | +| 108 | [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 | +| 109 | [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 | +| 110 | [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 | +| 111 | [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 | +| 112 | [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 | +| 113 | [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 | +| 114 | [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) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| -| 1 | [ML-1-Introduction-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-1-Introduction-Python.ipynb) | ML-1 (Python) : Introduction au Machine Learning… | Python 3 | READY | BETA | 30min | po-2023 | -| 2 | [ML-1-Introduction.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-1-Introduction.ipynb) | ML-1 : Introduction au Machine Learning avec… | .NET (C#) | READY | BETA | 45min | po-2023 | -| 3 | [ML-10-TSAD-Benchmark-Flaws-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-10-TSAD-Benchmark-Flaws-Python.ipynb) | ML-10 (Python) : l'illusion de progression en… | Python 3 | READY | BETA | 30min | po-2023 | -| 4 | [ML-11-MatrixProfile-Multidim-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-11-MatrixProfile-Multidim-Python.ipynb) | ML-11 : le Matrix Profile multidimensionnel, une… | Python 3 | READY | BETA | 45min | po-2023 | -| 5 | [ML-2-Data&Features-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-2-Data&Features-Python.ipynb) | ML-2 : Préparation des données et ingénierie des… | Python 3 | READY | BETA | 30min | po-2023 | -| 6 | [ML-2-Data&Features.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-2-Data&Features.ipynb) | ML-2 : Préparation des données et ingénierie des… | .NET (C#) | READY | BETA | 45min | po-2023 | -| 7 | [ML-3-Entrainement&AutoML.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-3-Entrainement&AutoML.ipynb) | ML-3 : Entraînement et AutoML | .NET (C#) | READY | BETA | 45min | po-2023 | -| 8 | [ML-3-Entrainement-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-3-Entrainement-Python.ipynb) | ML-3 (Python) : Entraînement et AutoML | Python 3 | READY | BETA | 30min | po-2023 | -| 9 | [ML-4-Evaluation-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-4-Evaluation-Python.ipynb) | ML-4 : Évaluation des modèles (Python / sklearn) | Python 3 | READY | BETA | 30min | po-2023 | -| 10 | [ML-4-Evaluation.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-4-Evaluation.ipynb) | ML-4 : Evaluation des modèles | .NET (C#) | READY | BETA | 2h+ | po-2023 | -| 11 | [ML-4b-ModelComparison-Validity-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-4b-ModelComparison-Validity-Python.ipynb) | ML-4b : Validité statistique des comparaisons de… | Python 3 | READY | BETA | 30min | po-2023 | -| 12 | [ML-5-TimeSeries-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-5-TimeSeries-Python.ipynb) | ML-5 (Python) : Prévision de séries temporelles… | Python 3 | READY | BETA | 30min | po-2023 | -| 13 | [ML-5-TimeSeries.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-5-TimeSeries.ipynb) | ML-5 : Time Series Forecasting avec ML.NET | .NET (C#) | READY | BETA | 45min | po-2023 | -| 14 | [ML-5b-Series-Temporelles-Classiques-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-5b-Series-Temporelles-Classiques-Python.ipynb) | ML-5b (Python) : Séries temporelles classiques —… | Python 3 | READY | BETA | 30min | po-2023 | -| 15 | [ML-6-ONNX-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-6-ONNX-Python.ipynb) | ML-6 (Python) : Intégration de modèles ONNX… | Python (coursia-ml-training) | READY | BETA | 30min | po-2023 | -| 16 | [ML-6-ONNX.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-6-ONNX.ipynb) | ML-6 : ONNX Model Integration avec ML.NET | .NET (C#) | READY | BETA | 45min | po-2023 | -| 17 | [ML-7-Recommendation-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-7-Recommendation-Python.ipynb) | ML-7 (Python) : Systèmes de recommandation par… | Python 3 | READY | BETA | 30min | po-2023 | -| 18 | [ML-7-Recommendation.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-7-Recommendation.ipynb) | ML-7 : Systèmes de Recommandation avec ML.NET | .NET (C#) | READY | BETA | 45min | po-2023 | -| 19 | [ML-8-Clustering-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-8-Clustering-Python.ipynb) | ML-8 (Python) : Clustering non-supervisé avec… | Python 3 | READY | BETA | 30min | po-2023 | -| 20 | [ML-8-Clustering.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-8-Clustering.ipynb) | ML-8 : Clustering non-supervise avec K-Means | .NET (C#) | READY | BETA | 45min | po-2023 | -| 21 | [ML-9-Anomaly-Detection-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-9-Anomaly-Detection-Python.ipynb) | ML-9 (Python) : Détection d'anomalies par PCA… | Python 3 | READY | BETA | 30min | po-2023 | -| 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 | +| 1 | [ML-01-Introduction-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-01-Introduction-Python.ipynb) | ML-01 (Python) : Introduction au Machine Learning… | Python 3 | READY | BETA | 30min | po-2023 | +| 2 | [ML-01-Introduction.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-01-Introduction.ipynb) | ML-01 : Introduction au Machine Learning avec… | .NET (C#) | READY | BETA | 45min | po-2023 | +| 3 | [ML-02-Data&Features-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-02-Data&Features-Python.ipynb) | ML-02 : Préparation des données et ingénierie des… | Python 3 | READY | BETA | 30min | po-2023 | +| 4 | [ML-02-Data&Features.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-02-Data&Features.ipynb) | ML-02 : Préparation des données et ingénierie des… | .NET (C#) | READY | BETA | 45min | po-2023 | +| 5 | [ML-03-Entrainement&AutoML-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-03-Entrainement&AutoML-Python.ipynb) | ML-03 (Python) : Entraînement et AutoML | Python 3 | READY | BETA | 30min | po-2023 | +| 6 | [ML-03-Entrainement&AutoML.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-03-Entrainement&AutoML.ipynb) | ML-03 : Entraînement et AutoML | .NET (C#) | READY | BETA | 45min | po-2023 | +| 7 | [ML-04-Evaluation-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-04-Evaluation-Python.ipynb) | ML-04 : Évaluation des modèles (Python / sklearn) | Python 3 | READY | BETA | 30min | po-2023 | +| 8 | [ML-04-Evaluation.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-04-Evaluation.ipynb) | ML-04 : Evaluation des modèles | .NET (C#) | READY | BETA | 2h+ | po-2023 | +| 9 | [ML-04b-ModelComparison-Validity-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-04b-ModelComparison-Validity-Python.ipynb) | ML-04b : Validité statistique des comparaisons de… | Python 3 | READY | BETA | 30min | po-2023 | +| 10 | [ML-05-TimeSeries-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-05-TimeSeries-Python.ipynb) | ML-05 (Python) : Prévision de séries temporelles… | Python 3 | READY | BETA | 30min | po-2023 | +| 11 | [ML-05-TimeSeries.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-05-TimeSeries.ipynb) | ML-05 : Time Series Forecasting avec ML.NET | .NET (C#) | READY | BETA | 45min | po-2023 | +| 12 | [ML-05b-Series-Temporelles-Classiques-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-05b-Series-Temporelles-Classiques-Python.ipynb) | ML-05b (Python) : Séries temporelles classiques —… | Python 3 | READY | BETA | 30min | po-2023 | +| 13 | [ML-06-ONNX-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-06-ONNX-Python.ipynb) | ML-06 (Python) : Intégration de modèles ONNX… | Python (coursia-ml-training) | READY | BETA | 30min | po-2023 | +| 14 | [ML-06-ONNX.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-06-ONNX.ipynb) | ML-06 : ONNX Model Integration avec ML.NET | .NET (C#) | READY | BETA | 45min | po-2023 | +| 15 | [ML-07-Recommendation-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-07-Recommendation-Python.ipynb) | ML-07 (Python) : Systèmes de recommandation par… | Python 3 | READY | BETA | 30min | po-2023 | +| 16 | [ML-07-Recommendation.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-07-Recommendation.ipynb) | ML-07 : Systèmes de Recommandation avec ML.NET | .NET (C#) | READY | BETA | 45min | po-2023 | +| 17 | [ML-08-Clustering-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-08-Clustering-Python.ipynb) | ML-08 (Python) : Clustering non-supervisé avec… | Python 3 | READY | BETA | 30min | po-2023 | +| 18 | [ML-08-Clustering.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-08-Clustering.ipynb) | ML-08 : Clustering non-supervise avec K-Means | .NET (C#) | READY | BETA | 45min | po-2023 | +| 19 | [ML-09-Anomaly-Detection-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-09-Anomaly-Detection-Python.ipynb) | ML-09 (Python) : Détection d'anomalies par PCA… | Python 3 | READY | BETA | 30min | po-2023 | +| 20 | [ML-09-Anomaly-Detection.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-09-Anomaly-Detection.ipynb) | ML-09 : Detection d'anomalies avec Randomized PCA | .NET (C#) | READY | BETA | 45min | po-2023 | +| 21 | [ML-09b-TSAD-Benchmark-Flaws-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-09b-TSAD-Benchmark-Flaws-Python.ipynb) | ML-09b (Python) : l'illusion de progression en… | Python 3 | READY | BETA | 30min | po-2023 | +| 22 | [ML-09c-MatrixProfile-Multidim-Python.ipynb](MyIA.AI.Notebooks/ML/ML.Net/ML-09c-MatrixProfile-Multidim-Python.ipynb) | ML-09c : le Matrix Profile multidimensionnel, une… | Python 3 | 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 (319 notebooks) — DEMO:5, READY:314 | ALPHA:9, BETA:305, DRAFT:5 +### SymbolicAI (327 notebooks) — DEMO:5, READY:322 | ALPHA:9, BETA:312, DRAFT:6 #### Racine (1) @@ -800,7 +814,7 @@ Total notebooks: 1376 | 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 (89) +#### Lean (96) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -808,91 +822,98 @@ Total notebooks: 1376 | 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 | [KNOTS-01-Conway-Proofs-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/KNOTS/KNOTS-01-Conway-Proofs-Lean-Python.ipynb) | Lean 17a — Conway, les Nœuds et la Preuve de… | Python 3.13.15 (CPython… | READY | BETA | 30min | po-2024 | -| 11 | [KNOTS-02-Invariants-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/KNOTS/KNOTS-02-Invariants-Python.ipynb) | Lean 17b — Invariants de Nœuds : Calcul et… | Python 3 | READY | BETA | 45min | po-2024 | -| 12 | [KNOTS-03-Companion-Formel-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/KNOTS/KNOTS-03-Companion-Formel-Lean-Python.ipynb) | Lean 17c — Le lake knot_lean par ses déclarations… | Python 3 | READY | BETA | 30min | po-2024 | -| 13 | [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 | -| 14 | [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 | -| 15 | [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 | -| 16 | [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 | -| 17 | [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 | -| 18 | [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 | -| 19 | [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 | -| 20 | [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 | -| 21 | [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 | -| 22 | [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 | -| 23 | [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 | -| 24 | [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 | -| 25 | [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 | -| 26 | [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 | -| 27 | [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 | -| 28 | [Lean-10b-LeanDojo-v2-Pantograph-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-10b-LeanDojo-v2-Pantograph-Lean-Python.ipynb) | Lean-10b — LeanDojo-v2 : du tracage a la recherche… | Python 3 (leandojo-v2) | READY | BETA | 30min | po-2024 | -| 29 | [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 | -| 30 | [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 | -| 31 | [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 | -| 32 | [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 | -| 33 | [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 | -| 34 | [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 | -| 35 | [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 | -| 36 | [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 | -| 37 | [Lean-13d-CHSH-Indeterminisme-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13d-CHSH-Indeterminisme-Native.ipynb) | Lean-13d : du CHSH au libre arbitre — la route… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 38 | [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 | -| 39 | [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 | -| 40 | [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 | -| 41 | [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 | -| 42 | [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 | DRAFT | 45min | po-2024 | -| 43 | [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 | -| 44 | [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 | -| 45 | [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 3.13.x (CPython… | READY | BETA | 45min | po-2024 | -| 46 | [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 | -| 47 | [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 | -| 48 | [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 | -| 49 | [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 | -| 50 | [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 | -| 51 | [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 | -| 52 | [Lean-16i-Translateur-Life.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16i-Translateur-Life.ipynb) | Lean-16i — Synthèse d'un translateur minuscule :… | Python 3.13.x (CPython… | READY | BETA | 15min | po-2024 | -| 53 | [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 | -| 54 | [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 | -| 55 | [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 | -| 56 | [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 | -| 57 | [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 | -| 58 | [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 | -| 59 | [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 | -| 60 | [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 | -| 61 | [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 | -| 62 | [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 | -| 63 | [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 | -| 64 | [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 | -| 65 | [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 | -| 66 | [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 | -| 67 | [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 | -| 68 | [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 | -| 69 | [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 | -| 70 | [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 | -| 71 | [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 | -| 72 | [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 | -| 73 | [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 | -| 74 | [Lean-37-Capstone-Serre100.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-37-Capstone-Serre100.ipynb) | Lean-37 : Capstone — la sous-série « Serre 100 » | Python 3.13.15 (CPython… | READY | BETA | 15min | po-2024 | -| 75 | [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 | -| 76 | [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 | -| 77 | [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 | -| 78 | [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 | -| 79 | [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 | -| 80 | [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 | -| 81 | [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 | -| 82 | [08-serre-dans-mathlib-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/08-serre-dans-mathlib-Lean.ipynb) | Serre dans Mathlib — tour guidé des cinq monuments | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 83 | [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 | -| 84 | [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 | -| 85 | [11-corps-quadratiques-reciprocite-quadratique.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/11-corps-quadratiques-reciprocite-quadratique.ipynb) | 11 — Corps quadratiques imaginaires, caractères de… | Python 3 | READY | BETA | 15min | po-2024 | -| 86 | [12-formes-quadratiques-binaires-nombre-classes.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/12-formes-quadratiques-binaires-nombre-classes.ipynb) | 12 - Formes quadratiques binaires et nombre de… | Python 3 | READY | BETA | 30min | po-2024 | -| 87 | [13-jacobi-kronecker-reciprocite-II.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/13-jacobi-kronecker-reciprocite-II.ipynb) | 13 - Loi de reciprocité quadratique II : symbole… | Python 3 | READY | BETA | 15min | po-2024 | -| 88 | [14-formes-quadratiques-composition-gauss.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/14-formes-quadratiques-composition-gauss.ipynb) | 14 - Composition des formes quadratiques binaires… | Python 3 | READY | BETA | 30min | po-2024 | -| 89 | [15-quatre-carres-lagrange.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/15-quatre-carres-lagrange.ipynb) | 15 - Théorème de Lagrange : tout entier est somme… | Python 3 | READY | BETA | 15min | po-2024 | +| 5 | [ANALYSE-05-KLS-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-05-KLS-Lean-Python.ipynb) | ANALYSE-05 : La conjecture KLS démontrée — digérer… | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | +| 6 | [ANALYSE-08-Ramsey-VdW.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-08-Ramsey-VdW.ipynb) | ANALYSE-08 : Ramsey et van der Waerden —… | Python 3 | READY | BETA | 30min | po-2024 | +| 7 | [ANALYSE-09-Tuilage-Aperiodique.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-09-Tuilage-Aperiodique.ipynb) | ANALYSE-09 : Un carreau de ℤ³ qui pave sans… | Python 3 | READY | BETA | 15min | po-2024 | +| 8 | [ANALYSE-09-Tuilage-Aperiodique_en.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-09-Tuilage-Aperiodique_en.ipynb) | ANALYSE-09: A single tile of Z^3 that tiles… | Python 3 | READY | BETA | 15min | po-2024 | +| 9 | [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 | +| 10 | [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 | +| 11 | [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 | +| 12 | [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 | +| 13 | [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 | +| 14 | [Geometry-05-Pont-Formel-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-05-Pont-Formel-Python.ipynb) | Geometry 05 — Prouvé par Gröbner, prouvé par le… | Python 3 | READY | BETA | 30min | po-2024 | +| 15 | [KNOTS-01-Conway-Proofs-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/KNOTS/KNOTS-01-Conway-Proofs-Lean-Python.ipynb) | Lean 17a — Conway, les Nœuds et la Preuve de… | Python 3.13.15 (CPython… | READY | BETA | 30min | po-2024 | +| 16 | [KNOTS-02-Invariants-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/KNOTS/KNOTS-02-Invariants-Python.ipynb) | Lean 17b — Invariants de Nœuds : Calcul et… | Python 3 | READY | BETA | 45min | po-2024 | +| 17 | [KNOTS-03-Companion-Formel-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/KNOTS/KNOTS-03-Companion-Formel-Lean-Python.ipynb) | Lean 17c — Le lake knot_lean par ses déclarations… | Python 3 | READY | BETA | 30min | po-2024 | +| 18 | [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 | +| 19 | [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 | +| 20 | [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 | +| 21 | [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 | +| 22 | [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 | +| 23 | [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 | +| 24 | [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 | +| 25 | [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 | +| 26 | [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 | +| 27 | [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 | +| 28 | [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 | +| 29 | [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 | +| 30 | [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 | +| 31 | [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 | +| 32 | [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 | +| 33 | [Lean-10b-LeanDojo-v2-Pantograph-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-10b-LeanDojo-v2-Pantograph-Lean-Python.ipynb) | Lean-10b — LeanDojo-v2 : du tracage a la recherche… | Python 3 (leandojo-v2) | READY | BETA | 30min | po-2024 | +| 34 | [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 | +| 35 | [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 | +| 36 | [Lean-12-Sensitivity-Theorem.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12-Sensitivity-Theorem.ipynb) | Lean-12 : Le Théorème de Sensibilité (Huang 2019) | Python 3.13.x (CPython… | READY | BETA | 30min | po-2024 | +| 37 | [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 | +| 38 | [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 | +| 39 | [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 | +| 40 | [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 | +| 41 | [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 | +| 42 | [Lean-13d-CHSH-Indeterminisme-Native.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13d-CHSH-Indeterminisme-Native.ipynb) | Lean-13d : du CHSH au libre arbitre — la route… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 43 | [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 | +| 44 | [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 | +| 45 | [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 | +| 46 | [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 | +| 47 | [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 | DRAFT | 45min | po-2024 | +| 48 | [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 | +| 49 | [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 | +| 50 | [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 3.13.x (CPython… | READY | BETA | 45min | po-2024 | +| 51 | [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 | +| 52 | [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 | +| 53 | [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 | +| 54 | [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 3.13.x (CPython… | READY | BETA | 45min | po-2024 | +| 55 | [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 | +| 56 | [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 | +| 57 | [Lean-16i-Translateur-Life.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16i-Translateur-Life.ipynb) | Lean-16i — Synthèse d'un translateur minuscule :… | Python 3.13.x (CPython… | READY | BETA | 15min | po-2024 | +| 58 | [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 | +| 59 | [Lean-17-Conway-Bridge-to-Knots-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17-Conway-Bridge-to-Knots-Python.ipynb) | Lean-17 : le pont Conway — du Game of Life (16) à… | Python 3 | READY | BETA | 15min | po-2024 | +| 60 | [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 | +| 61 | [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 | +| 62 | [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 | +| 63 | [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 | +| 64 | [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 | +| 65 | [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 | +| 66 | [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 | +| 67 | [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 | +| 68 | [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 | +| 69 | [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 | +| 70 | [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 | +| 71 | [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 | +| 72 | [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 | +| 73 | [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 | +| 74 | [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 | +| 75 | [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 | +| 76 | [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 | +| 77 | [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 | +| 78 | [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 | +| 79 | [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 | +| 80 | [Lean-37-Capstone-Serre100.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-37-Capstone-Serre100.ipynb) | Lean-37 : Capstone — la sous-série « Serre 100 » | Python 3.13.15 (CPython… | READY | BETA | 15min | po-2024 | +| 81 | [Lean-38-Capstone-Geometry-Lean-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-38-Capstone-Geometry-Lean-Python.ipynb) | Capstone Geometry — l'escalier d'entrée : de la… | Python 3 | READY | BETA | 30min | po-2024 | +| 82 | [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 | +| 83 | [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 | +| 84 | [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 | +| 85 | [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 | +| 86 | [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 | +| 87 | [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 | +| 88 | [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 | +| 89 | [08-serre-dans-mathlib-Lean.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/08-serre-dans-mathlib-Lean.ipynb) | Serre dans Mathlib — tour guidé des cinq monuments | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 90 | [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 | +| 91 | [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 | +| 92 | [11-corps-quadratiques-reciprocite-quadratique.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/11-corps-quadratiques-reciprocite-quadratique.ipynb) | 11 — Corps quadratiques imaginaires, caractères de… | Python 3 | READY | BETA | 15min | po-2024 | +| 93 | [12-formes-quadratiques-binaires-nombre-classes.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/12-formes-quadratiques-binaires-nombre-classes.ipynb) | 12 - Formes quadratiques binaires et nombre de… | Python 3 | READY | BETA | 30min | po-2024 | +| 94 | [13-jacobi-kronecker-reciprocite-II.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/13-jacobi-kronecker-reciprocite-II.ipynb) | 13 - Loi de reciprocité quadratique II : symbole… | Python 3 | READY | BETA | 15min | po-2024 | +| 95 | [14-formes-quadratiques-composition-gauss.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/14-formes-quadratiques-composition-gauss.ipynb) | 14 - Composition des formes quadratiques binaires… | Python 3 | READY | BETA | 30min | po-2024 | +| 96 | [15-quatre-carres-lagrange.ipynb](MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/15-quatre-carres-lagrange.ipynb) | 15 - Théorème de Lagrange : tout entier est somme… | Python 3 | READY | BETA | 15min | po-2024 | #### Planners (25) @@ -957,7 +978,7 @@ Total notebooks: 1376 | 27 | [SW-9-CSharp-JSONLD.ipynb](MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-9-CSharp-JSONLD.ipynb) | SW-9-CSharp-JSONLD -- JSON-LD avec dotNetRDF (twin… | .NET (C#) | READY | BETA | 45min | po-2024 | | 28 | [SW-9-Python-JSONLD.ipynb](MyIA.AI.Notebooks/SymbolicAI/SemanticWeb/SW-9-Python-JSONLD.ipynb) | SW-9-Python-JSONLD | Python 3 | READY | BETA | 1h | po-2024 | -#### SmartContracts (31) +#### SmartContracts (32) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -972,26 +993,27 @@ Total notebooks: 1376 | 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 | +| 12 | [SC-08b-MEV-LP-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-08b-MEV-LP-Python.ipynb) | SC-08b - MEV et rendement du fournisseur de… | Python 3 | READY | DRAFT | 30min | po-2024 | +| 13 | [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 | +| 14 | [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 | +| 15 | [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 | +| 16 | [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 | +| 17 | [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 | +| 18 | [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 | +| 19 | [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 | +| 20 | [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 | +| 21 | [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 | +| 22 | [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 | +| 23 | [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 | +| 24 | [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 | +| 25 | [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 | +| 26 | [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 | +| 27 | [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 | +| 28 | [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 | +| 29 | [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 | +| 30 | [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 | +| 31 | [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 | +| 32 | [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) @@ -1121,7 +1143,7 @@ Total notebooks: 1376 | 38 | [Tweety-12-Grounded-Via-TweetyProject-Python.ipynb](MyIA.AI.Notebooks/SymbolicAI/Tweety/Tweety-12-Grounded-Via-TweetyProject-Python.ipynb) | Argumentation Abstraite : Grounded Extension -… | 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 (120 notebooks) — DEMO:47, READY:73 | ALPHA:11, BETA:70, DRAFT:38, TEMPLATE:1 +### QuantConnect (121 notebooks) — DEMO:47, READY:74 | ALPHA:11, BETA:70, DRAFT:39, TEMPLATE:1 #### kelly_lean (6) @@ -1197,7 +1219,7 @@ Total notebooks: 1376 | 48 | [quantbook.ipynb](MyIA.AI.Notebooks/QuantConnect/projects/VIX-TermStructure/quantbook.ipynb) | Research QuantBook: VIX-TermStructure (Short… | Python 3 | READY | BETA | 45min | po-2026 | | 49 | [qc_top4_oos_extension.ipynb](MyIA.AI.Notebooks/QuantConnect/projects/_docs/qc_top4_oos_extension.ipynb) | Top-4 Sharpe > 0.5 Stratégies: OOS Deep-Dive… | Python 3 | READY | BETA | 15min | po-2026 | -#### Python (61) +#### Python (62) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -1221,7 +1243,7 @@ Total notebooks: 1376 | 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 | | 19 | [QC-Py-15-Parameter-Optimization.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-15-Parameter-Optimization.ipynb) | Objectifs d'Apprentissage | Python 3 | DEMO | DRAFT | 1h30 | po-2026 | | 20 | [QC-Py-16-Alternative-Data.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-16-Alternative-Data.ipynb) | QC-Py-16 - Alternative Data dans QuantConnect | Python 3 | DEMO | DRAFT | 45min | po-2026 | -| 21 | [QC-Py-17-Sentiment-Analysis.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-17-Sentiment-Analysis.ipynb) | Objectifs d'Apprentissage | Python 3 | DEMO | DRAFT | 1h | po-2026 | +| 21 | [QC-Py-17-Sentiment-Analysis.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-17-Sentiment-Analysis.ipynb) | Objectifs d'Apprentissage | Python 3 | READY | DRAFT | 1h | po-2026 | | 22 | [QC-Py-18-ML-Features-Engineering.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-18-ML-Features-Engineering.ipynb) | QC-Py-18 - Feature Engineering pour Machine… | Python 3 | READY | BETA | 1h | po-2026 | | 23 | [QC-Py-19-ML-Supervised-Classification.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-19-ML-Supervised-Classification.ipynb) | Objectifs d'Apprentissage | Python 3 | READY | BETA | 1h | po-2026 | | 24 | [QC-Py-20-ML-Regression-Prediction.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-20-ML-Regression-Prediction.ipynb) | Objectifs d'Apprentissage | Python 3 | READY | DRAFT | 1h | po-2026 | @@ -1246,26 +1268,27 @@ Total notebooks: 1376 | 43 | [QC-Py-35-RL-Portfolio-Construction.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-35-RL-Portfolio-Construction.ipynb) | QC-Py-35 - Reinforcement Learning pour la… | Python 3 | DEMO | ALPHA | 30min | po-2026 | | 44 | [QC-Py-40-PaperTrading-Binance.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-40-PaperTrading-Binance.ipynb) | QC-Py-40 : Paper Trading Binance - Mean Reversion… | Python 3 | DEMO | BETA | 45min | po-2026 | | 45 | [QC-Py-41-PaperTrading-IBKR.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-41-PaperTrading-IBKR.ipynb) | QC-Py-41 : Paper Trading IBKR - SP500 Momentum | Python 3 | DEMO | BETA | 45min | po-2026 | -| 46 | [QC-Py-Cloud-01-FinBERT-Sentiment.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-01-FinBERT-Sentiment.ipynb) | QC-Py-Cloud-01 : Analyse de Sentiment FinBERT sur… | Python 3 | DEMO | ALPHA | 30min | po-2026 | -| 47 | [QC-Py-Cloud-02-ML-Classification.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-02-ML-Classification.ipynb) | QC-Py-Cloud-02 : Classification de Texte et… | Python 3 | DEMO | ALPHA | 30min | po-2026 | -| 48 | [QC-Py-Cloud-03-Risk-Parity.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-03-Risk-Parity.ipynb) | QC-Py-Cloud-03 : Parite de Risque (Risk Parity) | Python 3 | READY | BETA | 30min | po-2026 | -| 49 | [QC-Py-Cloud-03b-RiskParity-Composite.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-03b-RiskParity-Composite.ipynb) | QC-Py-Cloud-03b — Risk Parity Composite… | Python 3 | DEMO | DRAFT | 15min | po-2026 | -| 50 | [QC-Py-Cloud-04-MeanReversion.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-04-MeanReversion.ipynb) | QC-Py-Cloud-04 — Mean Reversion on Sector ETFs | Python 3 | DEMO | DRAFT | 15min | po-2026 | -| 51 | [QC-Py-Cloud-05-MLP-Forecasting.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-05-MLP-Forecasting.ipynb) | QC-Py-Cloud-05 : Prevision par Reseau de Neurones… | Python 3 | DEMO | ALPHA | 30min | po-2026 | -| 52 | [QC-Py-Cloud-06-PCA-StatArb.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-06-PCA-StatArb.ipynb) | QC-Py-Cloud-06 — PCA Statistical Arbitrage Mean… | Python 3 | DEMO | DRAFT | 15min | po-2026 | -| 53 | [QC-Py-Cloud-07-TemporalCNN.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-07-TemporalCNN.ipynb) | QC-Py-Cloud-07 — Temporal CNN Direction Prediction | Python 3 | DEMO | DRAFT | 15min | po-2026 | -| 54 | [QC-Py-Cloud-08-ValueFactor-ZScore.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-08-ValueFactor-ZScore.ipynb) | Value Factor Z-Score — Sélection multi-facteurs… | Python 3 | DEMO | BETA | 15min | po-2026 | -| 55 | [QC-Py-Cloud-09-OptionWheel.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-09-OptionWheel.ipynb) | Option Wheel — Le paradoxe du win-rate eleve | Python 3 | DEMO | BETA | 15min | po-2026 | -| 56 | [QC-Py-Cloud-10-RL-DQN-Trading.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-10-RL-DQN-Trading.ipynb) | QC-Py-Cloud-10 : Reinforcement Learning - DQN… | Python 3 | DEMO | ALPHA | 30min | po-2026 | -| 57 | [QC-Py-Cloud-11-RegimeSwitching.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-11-RegimeSwitching.ipynb) | QC-Py-Cloud-11 — Regime Switching : Momentum in… | Python 3 | DEMO | DRAFT | 15min | po-2026 | -| 58 | [QC-Py-Cloud-12-SectorRotation-Momentum.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-12-SectorRotation-Momentum.ipynb) | QC-Py-Cloud-12 — Sector Rotation & Multi-Asset… | Python 3 | DEMO | DRAFT | 15min | po-2026 | -| 59 | [QC-Py-Cloud-13-VolTargeting.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-13-VolTargeting.ipynb) | QC-Py-Cloud-13 -- Volatility Targeting : Risk… | Python 3 | DEMO | DRAFT | 15min | po-2026 | -| 60 | [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 | -| 61 | [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 (110 notebooks) — DEMO:1, READY:109 | ALPHA:6, BETA:100, DRAFT:4 - -#### Racine (99) +| 46 | [QC-Py-42-Alpha-Mining-Evolution.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-42-Alpha-Mining-Evolution.ipynb) | QC-Py-42 - Alpha mining par evolution | Python 3 (CoursIA-2) | DEMO | DRAFT | 45min | po-2026 | +| 47 | [QC-Py-Cloud-01-FinBERT-Sentiment.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-01-FinBERT-Sentiment.ipynb) | QC-Py-Cloud-01 : Analyse de Sentiment FinBERT sur… | Python 3 | DEMO | ALPHA | 30min | po-2026 | +| 48 | [QC-Py-Cloud-02-ML-Classification.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-02-ML-Classification.ipynb) | QC-Py-Cloud-02 : Classification de Texte et… | Python 3 | DEMO | ALPHA | 30min | po-2026 | +| 49 | [QC-Py-Cloud-03-Risk-Parity.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-03-Risk-Parity.ipynb) | QC-Py-Cloud-03 : Parite de Risque (Risk Parity) | Python 3 | READY | BETA | 30min | po-2026 | +| 50 | [QC-Py-Cloud-03b-RiskParity-Composite.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-03b-RiskParity-Composite.ipynb) | QC-Py-Cloud-03b — Risk Parity Composite… | Python 3 | DEMO | DRAFT | 15min | po-2026 | +| 51 | [QC-Py-Cloud-04-MeanReversion.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-04-MeanReversion.ipynb) | QC-Py-Cloud-04 — Mean Reversion on Sector ETFs | Python 3 | DEMO | DRAFT | 15min | po-2026 | +| 52 | [QC-Py-Cloud-05-MLP-Forecasting.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-05-MLP-Forecasting.ipynb) | QC-Py-Cloud-05 : Prevision par Reseau de Neurones… | Python 3 | DEMO | ALPHA | 30min | po-2026 | +| 53 | [QC-Py-Cloud-06-PCA-StatArb.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-06-PCA-StatArb.ipynb) | QC-Py-Cloud-06 — PCA Statistical Arbitrage Mean… | Python 3 | DEMO | DRAFT | 15min | po-2026 | +| 54 | [QC-Py-Cloud-07-TemporalCNN.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-07-TemporalCNN.ipynb) | QC-Py-Cloud-07 — Temporal CNN Direction Prediction | Python 3 | DEMO | DRAFT | 15min | po-2026 | +| 55 | [QC-Py-Cloud-08-ValueFactor-ZScore.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-08-ValueFactor-ZScore.ipynb) | Value Factor Z-Score — Sélection multi-facteurs… | Python 3 | DEMO | BETA | 15min | po-2026 | +| 56 | [QC-Py-Cloud-09-OptionWheel.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-09-OptionWheel.ipynb) | Option Wheel — Le paradoxe du win-rate eleve | Python 3 | DEMO | BETA | 15min | po-2026 | +| 57 | [QC-Py-Cloud-10-RL-DQN-Trading.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-10-RL-DQN-Trading.ipynb) | QC-Py-Cloud-10 : Reinforcement Learning - DQN… | Python 3 | DEMO | ALPHA | 30min | po-2026 | +| 58 | [QC-Py-Cloud-11-RegimeSwitching.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-11-RegimeSwitching.ipynb) | QC-Py-Cloud-11 — Regime Switching : Momentum in… | Python 3 | DEMO | DRAFT | 15min | po-2026 | +| 59 | [QC-Py-Cloud-12-SectorRotation-Momentum.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-12-SectorRotation-Momentum.ipynb) | QC-Py-Cloud-12 — Sector Rotation & Multi-Asset… | Python 3 | DEMO | DRAFT | 15min | po-2026 | +| 60 | [QC-Py-Cloud-13-VolTargeting.ipynb](MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-13-VolTargeting.ipynb) | QC-Py-Cloud-13 -- Volatility Targeting : Risk… | Python 3 | DEMO | DRAFT | 15min | po-2026 | +| 61 | [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 | +| 62 | [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 (113 notebooks) — DEMO:1, READY:112 | ALPHA:6, BETA:102, DRAFT:5 + +#### Racine (101) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -1333,43 +1356,45 @@ Total notebooks: 1376 | 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 | 1h | po-2024 | -| 94 | [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 | -| 95 | [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 | -| 96 | [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 | -| 97 | [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 | -| 98 | [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 | -| 99 | [GameTheory-20e-Perplexite-Structurelle-Hashlife-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-20e-Perplexite-Structurelle-Hashlife-Python.ipynb) | GameTheory-20e -- Perplexite structurelle Hashlife… | Python 3 | READY | BETA | 15min | po-2024 | - -#### SocialChoice (11) +| 65 | [GameTheory-13e-Revision-Croyances-Adversaire-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-13e-Revision-Croyances-Adversaire-Python.ipynb) | GameTheory-13e : Réviser un modèle d'adversaire --… | Python (coursia-ml-training) | READY | BETA | 30min | po-2024 | +| 66 | [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 | +| 67 | [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 | +| 68 | [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 | +| 69 | [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 | +| 70 | [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 | +| 71 | [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 | +| 72 | [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 | +| 73 | [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 | +| 74 | [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 | +| 75 | [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 | +| 76 | [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 | +| 77 | [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 | +| 78 | [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 | +| 79 | [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 | +| 80 | [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 | +| 81 | [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 | +| 82 | [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 | +| 83 | [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 | +| 84 | [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 | +| 85 | [GameTheory-16g-Populations-Othman-Sandholm-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-16g-Populations-Othman-Sandholm-Python.ipynb) | GameTheory-16g : Populations Othman-Sandholm —… | Python 3 | READY | DRAFT | 30min | po-2024 | +| 86 | [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 | +| 87 | [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 | +| 88 | [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 | +| 89 | [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 | +| 90 | [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 | +| 91 | [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 | +| 92 | [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 | +| 93 | [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 | +| 94 | [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 | +| 95 | [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 | 1h | po-2024 | +| 96 | [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 | +| 97 | [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 | +| 98 | [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 | +| 99 | [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 | +| 100 | [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 | +| 101 | [GameTheory-20e-Perplexite-Structurelle-Hashlife-Python.ipynb](MyIA.AI.Notebooks/GameTheory/GameTheory-20e-Perplexite-Structurelle-Hashlife-Python.ipynb) | GameTheory-20e -- Perplexite structurelle Hashlife… | Python 3 | READY | BETA | 15min | po-2024 | + +#### SocialChoice (12) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -1384,6 +1409,7 @@ Total notebooks: 1376 | 9 | [06-Mobius-Aggregation-Pouvoir-Manipulation.ipynb](MyIA.AI.Notebooks/GameTheory/SocialChoice/06-Mobius-Aggregation-Pouvoir-Manipulation.ipynb) | SocialChoice-06 : Mobius sur le treillis des… | Python 3 | READY | BETA | 15min | po-2024 | | 10 | [07-Committees-Core.ipynb](MyIA.AI.Notebooks/GameTheory/SocialChoice/07-Committees-Core.ipynb) | 07 - Élections de comité par approbation : le core… | Python 3 | READY | BETA | 30min | po-2024 | | 11 | [08-Kemeny-RankedPairs-Dodgson.ipynb](MyIA.AI.Notebooks/GameTheory/SocialChoice/08-Kemeny-RankedPairs-Dodgson.ipynb) | SocialChoice 08 - Kemeny, Ranked Pairs et Dodgson… | Python 3 | READY | ALPHA | 30min | po-2024 | +| 12 | [09-Committees-STV-Monroe-ChamberlinCourant.ipynb](MyIA.AI.Notebooks/GameTheory/SocialChoice/09-Committees-STV-Monroe-ChamberlinCourant.ipynb) | 09 - Comites multi-vainqueurs : STV, Monroe et… | Python 3 | READY | BETA | 30min | po-2024 | ### Sudoku (38 notebooks) — DEMO:1, READY:37 | BETA:38 @@ -1430,7 +1456,7 @@ Total notebooks: 1376 | 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-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 (78 notebooks) — READY:78 | ALPHA:2, BETA:75, DRAFT:1 +### Probas (83 notebooks) — READY:83 | ALPHA:3, BETA:76, DRAFT:4 #### Racine (1) @@ -1438,16 +1464,20 @@ Total notebooks: 1376 |---|----------|-------|--------|--------|----------|----------|-------| | 1 | [Probas-KLS-Concentration.ipynb](MyIA.AI.Notebooks/Probas/Probas-KLS-Concentration.ipynb) | Probas-KLS-Concentration : gap spectral, constante… | Python 3 | READY | BETA | 45min | po-2023 | -#### Applications (4) +#### Applications (8) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| | 1 | [Percolation-01-Supercritique-Python.ipynb](MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-01-Supercritique-Python.ipynb) | Percolation supercritique : le géant au-dessus du… | Python 3 | READY | ALPHA | 30min | po-2023 | | 2 | [Percolation-02-Lean.ipynb](MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-02-Lean.ipynb) | Percolation-02-Lean — le noyau fini de… | Lean 4 (WSL, percolation) | READY | BETA | 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 | +| 3 | [Percolation-03-Critique-Python.ipynb](MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-03-Critique-Python.ipynb) | Percolation au point critique : exposants finis et… | Python 3 | READY | BETA | 15min | po-2023 | +| 4 | [Percolation-03b-Critique-L128-L256.ipynb](MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-03b-Critique-L128-L256.ipynb) | Percolation 03b — extensions L=128, L=256 (c.1105) | Python 3 | READY | DRAFT | 30min | po-2023 | +| 5 | [Percolation-03c-Critique-L512.ipynb](MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-03c-Critique-L512.ipynb) | Percolation 03c — extension L=512 (c.1106) | Python 3 | READY | DRAFT | 15min | po-2023 | +| 6 | [Percolation-04-Sharpness-Python.ipynb](MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-04-Sharpness-Python.ipynb) | Percolation 04 — Sharpness (palier 4, c.1108) | Python 3 | READY | DRAFT | 30min | po-2023 | +| 7 | [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 | +| 8 | [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 (32) +#### DecisionTheory (33) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -1456,33 +1486,34 @@ Total notebooks: 1376 | 3 | [Actuariat-03-Actuarial-Credibility.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Actuariat/Actuariat-03-Actuarial-Credibility.ipynb) | Actuariat-03 — Crédibilité actuarielle de… | Python 3 (ipykernel) | READY | BETA | 30min | po-2023 | | 4 | [Actuariat-04-Ruine-Lundberg.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Actuariat/Actuariat-04-Ruine-Lundberg.ipynb) | Actuariat-04 : Ruine et capital — le processus de… | Python 3 (ipykernel) | READY | BETA | 30min | po-2023 | | 5 | [Actuariat-05-Valeur-Info-Souscription.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Actuariat/Actuariat-05-Valeur-Info-Souscription.ipynb) | Actuariat-05 — Valeur de l'Information en… | Python 3 | READY | BETA | 30min | po-2023 | -| 6 | [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 | -| 7 | [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 | -| 8 | [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 | -| 9 | [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 | -| 10 | [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 | -| 11 | [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 | -| 12 | [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 | -| 13 | [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 | -| 14 | [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 | -| 15 | [DecInfer-02-Lean-ExpectedUtility.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-02-Lean-ExpectedUtility.ipynb) | DecInfer-02-Théorème de représentation de von… | Lean 4 (WSL) | READY | BETA | 15min | po-2023 | -| 16 | [DecInfer-02b-Lean-Coherence.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-02b-Lean-Coherence.ipynb) | DecInfer-02b-Lean-Coherence : Dutch Book et bornes… | Lean 4 (WSL) | READY | BETA | 15min | po-2023 | -| 17 | [DecInfer-03-Utility-Money.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-03-Utility-Money.ipynb) | DecInfer-03-Utility-Money : Utilite de l'Argent et… | .NET (C#) | READY | BETA | 1h | po-2023 | -| 18 | [DecInfer-04-Multi-Attribute.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-04-Multi-Attribute.ipynb) | DecInfer-04-Multi-Attribute : Utilite… | .NET (C#) | READY | BETA | 1h | po-2023 | -| 19 | [DecInfer-05-Decision-Networks.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-05-Decision-Networks.ipynb) | DecInfer-05-Decision-Networks : Reseaux de… | .NET (C#) | READY | BETA | 45min | po-2023 | -| 20 | [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 | -| 21 | [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 | -| 22 | [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 | -| 23 | [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 | -| 24 | [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 | -| 25 | [DecPyMC-08-Actuariat-Capstone.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-08-Actuariat-Capstone.ipynb) | DecPyMC-08 : Capstone — la sous-série Actuariat | Python 3 | READY | BETA | 15min | po-2023 | -| 26 | [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 | -| 27 | [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 | -| 28 | [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 | -| 29 | [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 | -| 30 | [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 | -| 31 | [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 | -| 32 | [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 | +| 6 | [CausalBridges-00-PearlLadder-Intro-Python.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-00-PearlLadder-Intro-Python.ipynb) | CausalBridges-00 — Du graphe causal a l'echelle de… | Python 3 | READY | ALPHA | 30min | po-2023 | +| 7 | [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 | +| 8 | [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 | +| 9 | [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 | +| 10 | [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 | +| 11 | [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 | +| 12 | [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 | +| 13 | [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 | +| 14 | [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 | +| 15 | [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 | +| 16 | [DecInfer-02-Lean-ExpectedUtility.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-02-Lean-ExpectedUtility.ipynb) | DecInfer-02-Théorème de représentation de von… | Lean 4 (WSL) | READY | BETA | 15min | po-2023 | +| 17 | [DecInfer-02b-Lean-Coherence.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-02b-Lean-Coherence.ipynb) | DecInfer-02b-Lean-Coherence : Dutch Book et bornes… | Lean 4 (WSL) | READY | BETA | 15min | po-2023 | +| 18 | [DecInfer-03-Utility-Money.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-03-Utility-Money.ipynb) | DecInfer-03-Utility-Money : Utilite de l'Argent et… | .NET (C#) | READY | BETA | 1h | po-2023 | +| 19 | [DecInfer-04-Multi-Attribute.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-04-Multi-Attribute.ipynb) | DecInfer-04-Multi-Attribute : Utilite… | .NET (C#) | READY | BETA | 1h | po-2023 | +| 20 | [DecInfer-05-Decision-Networks.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-05-Decision-Networks.ipynb) | DecInfer-05-Decision-Networks : Reseaux de… | .NET (C#) | READY | BETA | 45min | po-2023 | +| 21 | [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 | +| 22 | [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 | +| 23 | [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 | +| 24 | [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 | +| 25 | [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 | +| 26 | [DecPyMC-08-Actuariat-Capstone.ipynb](MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-08-Actuariat-Capstone.ipynb) | DecPyMC-08 : Capstone — la sous-série Actuariat | Python 3 | READY | BETA | 15min | po-2023 | +| 27 | [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 | +| 28 | [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 | +| 29 | [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 | +| 30 | [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 | +| 31 | [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 | +| 32 | [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 | +| 33 | [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 | #### Infer (21) @@ -1535,7 +1566,7 @@ Total notebooks: 1376 | 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 (94 notebooks) — DEMO:6, READY:88 | ALPHA:1, BETA:81, DRAFT:12 +### IIT (99 notebooks) — DEMO:7, READY:92 | ALPHA:2, BETA:83, DRAFT:14 #### Racine (6) @@ -1548,7 +1579,7 @@ Total notebooks: 1376 | 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 (88) +#### ICT-Series (93) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -1597,49 +1628,54 @@ Total notebooks: 1376 | 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 | 30min | 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-41b-Crosscoder-Distillation-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-41b-Crosscoder-Distillation-Python.ipynb) | ICT-41b — 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-42b-InoculationBifurcation-9B-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-42b-InoculationBifurcation-9B-Python.ipynb) | ICT-42b — Inoculation et bifurcation : la… | Python 3 | READY | DRAFT | 45min | po-2025 | -| 72 | [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 | -| 73 | [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 | -| 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-47-PainAxisDistillation-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-47-PainAxisDistillation-Python.ipynb) | ICT-47 — L'axe douleur : une direction linéaire… | Python 3 (py310-gpu) | DEMO | BETA | 1h | po-2025 | -| 76 | [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 | -| 77 | [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 | -| 78 | [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 | -| 79 | [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 | -| 80 | [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 | -| 81 | [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 | -| 82 | [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 | -| 83 | [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 | -| 84 | [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 | -| 85 | [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 | -| 86 | [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 | -| 87 | [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 | -| 88 | [ICT-Synthese-CrossSubstrat.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Synthese-CrossSubstrat.ipynb) | ICT-Synthèse — un seul appareil de mesure, cinq… | Python 3.9 (PyPhi/IIT) | READY | BETA | 45min | po-2025 | +| 46 | [ICT-22c-GeometryOfTruth-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-22c-GeometryOfTruth-Python.ipynb) | ICT-22c — La géométrie de la vérité : une… | coursia-ml-training | READY | BETA | 45min | po-2025 | +| 47 | [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 | 30min | po-2025 | +| 48 | [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 | +| 49 | [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 | +| 50 | [ICT-25b-StratificationInterTailles-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-25b-StratificationInterTailles-Python.ipynb) | ICT-25b — Stratification inter-tailles des… | Python 3 | READY | DRAFT | 15min | po-2025 | +| 51 | [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 | +| 52 | [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 | +| 53 | [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 | +| 54 | [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 | +| 55 | [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 | +| 56 | [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 | +| 57 | [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 | +| 58 | [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 | +| 59 | [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 | +| 60 | [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 | +| 61 | [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 | +| 62 | [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 | +| 63 | [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 | +| 64 | [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 | +| 65 | [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 | +| 66 | [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 | +| 67 | [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 | +| 68 | [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 | +| 69 | [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 | +| 70 | [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 | +| 71 | [ICT-41b-Crosscoder-Distillation-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-41b-Crosscoder-Distillation-Python.ipynb) | ICT-41b — Crosscoder : diffuser deux modèles,… | coursia-ml-training | READY | BETA | 45min | po-2025 | +| 72 | [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 | +| 73 | [ICT-42b-InoculationBifurcation-9B-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-42b-InoculationBifurcation-9B-Python.ipynb) | ICT-42b — Inoculation et bifurcation : la… | Python 3 | READY | DRAFT | 45min | po-2025 | +| 74 | [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 | +| 75 | [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 | +| 76 | [ICT-47-PainAxisDistillation-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-47-PainAxisDistillation-Python.ipynb) | ICT-47 — L'axe douleur : une direction linéaire… | Python 3 (py310-gpu) | DEMO | BETA | 1h | po-2025 | +| 77 | [ICT-47b-PainAxisInstrument-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-47b-PainAxisInstrument-Python.ipynb) | ICT-47b — L'instrument change-t-il la géométrie ? | Python 3 (ipykernel) | DEMO | DRAFT | 30min | po-2025 | +| 78 | [ICT-48-Onset9B-Aggregate-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-48-Onset9B-Aggregate-Python.ipynb) | ICT-48 — Onset/SAE Qwen3.5-9B-Base, agregat 4… | Python 3 | READY | ALPHA | 30min | po-2025 | +| 79 | [ICT-48-WolframClasses-ThermoSignature-Python.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-48-WolframClasses-ThermoSignature-Python.ipynb) | ICT-48 -- Origami Wolfram pli 2 : 4 classes vs… | Python 3 | READY | BETA | 30min | po-2025 | +| 80 | [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 | +| 81 | [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 | +| 82 | [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 | +| 83 | [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 | +| 84 | [ICT-Dissociation-DehaeneF2-SelfReport.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-DehaeneF2-SelfReport.ipynb) | ICT -- Dissociation F2 Dehaene : le self-model… | Python 3 | READY | BETA | 30min | po-2025 | +| 85 | [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 | +| 86 | [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 | +| 87 | [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 | +| 88 | [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 | +| 89 | [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 | +| 90 | [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 | +| 91 | [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 | +| 92 | [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 | +| 93 | [ICT-Synthese-CrossSubstrat.ipynb](MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Synthese-CrossSubstrat.ipynb) | ICT-Synthèse — un seul appareil de mesure, cinq… | Python 3.9 (PyPhi/IIT) | READY | BETA | 45min | po-2025 | ### RL (35 notebooks) — DEMO:4, READY:31 | ALPHA:3, BETA:30, DRAFT:2 @@ -1711,9 +1747,9 @@ Total notebooks: 1376 | 1 | [SmartGrid-Energy.ipynb](MyIA.AI.Notebooks/CaseStudies/SmartGrid-Energy/solution/SmartGrid-Energy.ipynb) | CC3 : SmartGrid - Ordonnancement de la production… | Python 3 | READY | BETA | 30min | | | 2 | [SmartGrid-Energy.ipynb](MyIA.AI.Notebooks/CaseStudies/SmartGrid-Energy/student/SmartGrid-Energy.ipynb) | CC3 : SmartGrid - Ordonnancement de la production… | Python 3 | READY | BETA | 30min | | -### Complexity (13 notebooks) — READY:13 | BETA:13 +### Complexity (14 notebooks) — READY:14 | BETA:14 -#### Racine (13) +#### Racine (14) | # | Notebook | Title | Kernel | Status | Maturity | Duration | Owner | |---|----------|-------|--------|--------|----------|----------|-------| @@ -1728,8 +1764,9 @@ Total notebooks: 1376 | 9 | [Complexity-04d-Secretaire-Matroidal-Python.ipynb](MyIA.AI.Notebooks/Complexity/Complexity-04d-Secretaire-Matroidal-Python.ipynb) | RL 18 - Le secrétaire matroïdal : la conjecture… | Python 3 (ipykernel) | READY | BETA | 30min | | | 10 | [Complexity-05-CountingHarder-Permanent.ipynb](MyIA.AI.Notebooks/Complexity/Complexity-05-CountingHarder-Permanent.ipynb) | Complexity-05 — Compter est plus dur que vérifier… | Python 3 | READY | BETA | 30min | | | 11 | [Complexity-05b-AaronsonArkhipov-PermanenteBosonSampling.ipynb](MyIA.AI.Notebooks/Complexity/Complexity-05b-AaronsonArkhipov-PermanenteBosonSampling.ipynb) | Complexity-05b — La permanente, frontière… | Python 3 | READY | BETA | 30min | | -| 12 | [Complexity-06b-AaronsonGottesman-Dequantification-Python.ipynb](MyIA.AI.Notebooks/Complexity/Complexity-06b-AaronsonGottesman-Dequantification-Python.ipynb) | Complexity-06b — Déquantifier les suprématies… | Python 3 | READY | BETA | 30min | | -| 13 | [Complexity-07-KolmogorovBornee-Sequences-Python.ipynb](MyIA.AI.Notebooks/Complexity/Complexity-07-KolmogorovBornee-Sequences-Python.ipynb) | Complexity-07 — Complexité de Kolmogorov bornée :… | Python 3 (coursia-ml-training) | READY | BETA | 30min | | +| 12 | [Complexity-06-Simuler-Circuit-Quantique-Classiquement-Python.ipynb](MyIA.AI.Notebooks/Complexity/Complexity-06-Simuler-Circuit-Quantique-Classiquement-Python.ipynb) | Complexity-06 — Simuler un circuit quantique… | Python 3 | READY | BETA | 15min | | +| 13 | [Complexity-06b-AaronsonGottesman-Dequantification-Python.ipynb](MyIA.AI.Notebooks/Complexity/Complexity-06b-AaronsonGottesman-Dequantification-Python.ipynb) | Complexity-06b — Déquantifier les suprématies… | Python 3 | READY | BETA | 30min | | +| 14 | [Complexity-07-KolmogorovBornee-Sequences-Python.ipynb](MyIA.AI.Notebooks/Complexity/Complexity-07-KolmogorovBornee-Sequences-Python.ipynb) | Complexity-07 — Complexité de Kolmogorov bornée :… | Python 3 (coursia-ml-training) | READY | BETA | 30min | | ### Compression (1 notebooks) — READY:1 | BETA:1 @@ -1763,8 +1800,8 @@ Total notebooks: 1376 ## Requirements -- **API**: 200 notebooks -- **GPU**: 191 notebooks -- **Cloud**: 124 notebooks -- **WSL**: 126 notebooks -- **Local**: 821 notebooks \ No newline at end of file +- **API**: 202 notebooks +- **GPU**: 194 notebooks +- **Cloud**: 125 notebooks +- **WSL**: 133 notebooks +- **Local**: 841 notebooks \ No newline at end of file diff --git a/MyIA.AI.Notebooks/GameTheory/README.md b/MyIA.AI.Notebooks/GameTheory/README.md index c1fcc76044..226307a693 100644 --- a/MyIA.AI.Notebooks/GameTheory/README.md +++ b/MyIA.AI.Notebooks/GameTheory/README.md @@ -4,9 +4,9 @@ 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/GameTheory/SocialChoice/README.md b/MyIA.AI.Notebooks/GameTheory/SocialChoice/README.md index 82a8b01177..2a3b6ef45a 100644 --- a/MyIA.AI.Notebooks/GameTheory/SocialChoice/README.md +++ b/MyIA.AI.Notebooks/GameTheory/SocialChoice/README.md @@ -2,9 +2,9 @@ La théorie du choix social étudie comment agréger des préférences individuelles en une décision collective. Ses résultats les plus célèbres sont des **théorèmes d'impossibilité** : le théorème d'Arrow (1951) montre qu'aucune règle de vote ne peut satisfaire simultanément des axiomes "raisonnables" (Pareto, IIA, non-dictature) dès que 3 alternatives ou plus sont en jeu ; le théorème de Sen (1970) démontre un conflit fondamental entre liberté individuelle et efficacité collective. diff --git a/MyIA.AI.Notebooks/GenAI/README.md b/MyIA.AI.Notebooks/GenAI/README.md index b7d5b5ed49..ee157b729c 100644 --- a/MyIA.AI.Notebooks/GenAI/README.md +++ b/MyIA.AI.Notebooks/GenAI/README.md @@ -419,7 +419,7 @@ Trois sous-dossiers complètent la série sans être des notebooks : diff --git a/MyIA.AI.Notebooks/IIT/ICT-Series/README.md b/MyIA.AI.Notebooks/IIT/ICT-Series/README.md index ee91508d3b..3e114aac66 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 980ac9bc2c..19a2d372d2 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 bf8bae56d3..897974dcfc 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 57730559de..4b98b1ab63 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 (total de la famille, 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 la **répartition par kernel** (C#/.NET vs Python vs Lean 4) au sein d'une sous-série — la décomposition **technique** par interpréteur, que le marqueur n'agrège pas —, la source est la lecture directe des `metadata.kernelspec` des notebooks : ces volumes dérivent à chaque ajout et **aucun chiffre n'est maintenu ici en prose**. 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 lors du prochain passage. diff --git a/MyIA.AI.Notebooks/QuantConnect/Python/README.md b/MyIA.AI.Notebooks/QuantConnect/Python/README.md index 4c572db95e..43d8149094 100644 --- a/MyIA.AI.Notebooks/QuantConnect/Python/README.md +++ b/MyIA.AI.Notebooks/QuantConnect/Python/README.md @@ -1,8 +1,8 @@ # QuantConnect Python Notebooks diff --git a/MyIA.AI.Notebooks/QuantConnect/README.md b/MyIA.AI.Notebooks/QuantConnect/README.md index 90d592b94c..0a1ff3a55a 100644 --- a/MyIA.AI.Notebooks/QuantConnect/README.md +++ b/MyIA.AI.Notebooks/QuantConnect/README.md @@ -2,9 +2,9 @@ > **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 87136aa4e6..0416010e44 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/SymbolicAI/Lean/README.md b/MyIA.AI.Notebooks/SymbolicAI/Lean/README.md index 53a4de08d5..a3094b79dc 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 bbecb35fca..930c474961 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/SmartContracts/README.md b/MyIA.AI.Notebooks/SymbolicAI/SmartContracts/README.md index 313baaaa28..76d5235949 100644 --- a/MyIA.AI.Notebooks/SymbolicAI/SmartContracts/README.md +++ b/MyIA.AI.Notebooks/SymbolicAI/SmartContracts/README.md @@ -4,9 +4,9 @@ Série de notebooks éducatifs couvrant les fondements cryptographiques, le développement Solidity, les tests, la cryptographie avancée (ZKP, HE, vote vérifiable), et les blockchains alternatives. diff --git a/_quarto.yml b/_quarto.yml index 5cedc15138..a6307da6cf 100644 --- a/_quarto.yml +++ b/_quarto.yml @@ -286,6 +286,7 @@ project: - "MyIA.AI.Notebooks/QuantConnect/projects/Congress-Trades-Copy/README.md" - "MyIA.AI.Notebooks/QuantConnect/projects/Corrective-AI/README.md" - "MyIA.AI.Notebooks/QuantConnect/projects/Crypto-LSTM-Prediction/README.md" + - "MyIA.AI.Notebooks/QuantConnect/projects/Crypto-Momentum-TopN/README.md" - "MyIA.AI.Notebooks/QuantConnect/projects/Crypto-MultiCanal/README.md" - "MyIA.AI.Notebooks/QuantConnect/projects/CSharp-BTC-EMA-Cross/README.md" - "MyIA.AI.Notebooks/QuantConnect/projects/CSharp-BTC-MACD-ADX/README.md" @@ -661,6 +662,7 @@ project: - "docs/ledgers/15159-wan-video-inv.md" - "docs/ledgers/15573-cadrage-granulaire.md" - "docs/ledgers/15615-gradation-foundations.md" + - "docs/ledgers/15615-gradation-fournee-a.md" - "docs/ledgers/16473-consolidation-acceptance-2-log.md" - "docs/ledgers/17375-md-content-loss-justified.md" - "docs/ledgers/18741-qualification-14-notebooks.md" @@ -1705,6 +1707,7 @@ project: - "MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-35-RL-Portfolio-Construction.ipynb" - "MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-40-PaperTrading-Binance.ipynb" - "MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-41-PaperTrading-IBKR.ipynb" + - "MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-42-Alpha-Mining-Evolution.ipynb" - "MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-01-FinBERT-Sentiment.ipynb" - "MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-02-ML-Classification.ipynb" - "MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-Cloud-03-Risk-Parity.ipynb" diff --git a/docs/archive/reference/HEALTH_DASHBOARD.md b/docs/archive/reference/HEALTH_DASHBOARD.md index 6ed0a92ee1..b9c215168f 100644 --- a/docs/archive/reference/HEALTH_DASHBOARD.md +++ b/docs/archive/reference/HEALTH_DASHBOARD.md @@ -1,67 +1,67 @@ # Tableau de santé du dépôt — snapshot dérivé du catalogue -> Snapshot statique généré depuis `COURSE_CATALOG.generated.json` (date catalogue : **2026-10-08**). +> Snapshot statique généré depuis `COURSE_CATALOG.generated.json` (date catalogue : **2026-10-11**). > 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`. -**1376** notebooks référencés au catalogue. +**1407** notebooks référencés au catalogue. ## État global | Statut | Count | % | |--------|-------|---| -| READY | 1162 | 84.4% | -| DEMO | 212 | 15.4% | +| READY | 1190 | 84.6% | +| DEMO | 215 | 15.3% | | BROKEN | 2 | 0.1% | ## Exigences d'environnement (badges) | Exigence | Notebooks concernés | |----------|---------------------| -| **local** (exécutable sans GPU/cloud/WSL) | 821 | -| WSL requis | 126 | -| GPU requis | 191 | -| Cloud requis (QC / GenAI Docker) | 124 | -| API key requise | 200 | +| **local** (exécutable sans GPU/cloud/WSL) | 841 | +| WSL requis | 133 | +| GPU requis | 194 | +| Cloud requis (QC / GenAI Docker) | 125 | +| API key requise | 202 | ## Distribution par série | Série | READY | DEMO | BROKEN | Total | % READY | |-------|-------|------|--------|-------|---------| | CaseStudies | 6 | 0 | 0 | 6 | 100% | -| Complexity | 13 | 0 | 0 | 13 | 100% | +| Complexity | 14 | 0 | 0 | 14 | 100% | | Compression | 1 | 0 | 0 | 1 | 100% | -| GameTheory | 109 | 1 | 0 | 110 | 99% | -| GenAI | 138 | 127 | 2 | 267 | 52% | -| IIT | 88 | 6 | 0 | 94 | 94% | -| ML | 110 | 21 | 0 | 131 | 84% | +| GameTheory | 112 | 1 | 0 | 113 | 99% | +| GenAI | 138 | 129 | 2 | 269 | 51% | +| IIT | 92 | 7 | 0 | 99 | 93% | +| ML | 116 | 21 | 0 | 137 | 85% | | NLP | 5 | 0 | 0 | 5 | 100% | -| Probas | 78 | 0 | 0 | 78 | 100% | -| QuantConnect | 73 | 47 | 0 | 120 | 61% | +| Probas | 83 | 0 | 0 | 83 | 100% | +| QuantConnect | 74 | 47 | 0 | 121 | 61% | | RL | 31 | 4 | 0 | 35 | 89% | | Search | 157 | 0 | 0 | 157 | 100% | | Sudoku | 37 | 1 | 0 | 38 | 97% | -| SymbolicAI | 314 | 5 | 0 | 319 | 98% | +| SymbolicAI | 322 | 5 | 0 | 327 | 98% | | cross-series | 2 | 0 | 0 | 2 | 100% | ## Kernels | Kernel | Count | |--------|-------| -| Python 3 | 895 | +| Python 3 | 919 | | .NET (C#) | 268 | -| Python 3 (ipykernel) | 49 | -| Lean 4 (WSL) | 49 | +| Python 3 (ipykernel) | 51 | +| Lean 4 (WSL) | 50 | | Python 3 (coursia-ml-training) | 18 | -| Python (coursia-ml-training) | 17 | +| Python (coursia-ml-training) | 18 | | coursia-ml-training | 12 | | unknown | 7 | | Python 3 (WSL) | 6 | +| Python 3.13.x (CPython canonique serie Lean) | 5 | | Python 3.9 (PyPhi/IIT) | 4 | | Python 3 (PyPhi/IIT) | 4 | | Coursia ML Training | 3 | | Lean 4 | 3 | -| Python 3.13.x (CPython canonique serie Lean) | 3 | | Python (GameTheory WSL + OpenSpiel) | 2 | | base | 2 | | Python 3 (coursia2) | 2 | @@ -84,6 +84,7 @@ | Py310-Gpu | 1 | | Lean 4 (WSL, percolation) | 1 | | Python 3 (PyMC 3.11) | 1 | +| Python 3 (CoursIA-2) | 1 | | Foundation-Py-Default | 1 | | .venv (3.14.3) | 1 | | Lean 4 (WSL, grothendieck-16200) | 1 | diff --git a/docs/curriculum/genai.md b/docs/curriculum/genai.md index aca6352f0f..924ac2f8f8 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 | 246 | +| Notebooks | 247 | | PRODUCTION | 0 | -| BETA | 223 | +| BETA | 224 | | ALPHA | 23 | ## GenAI/00-GenAI-Environment (7 notebooks) @@ -37,6 +37,12 @@ Génération d'images (DALL-E, Stable Diffusion, Qwen, ComfyUI), synthèse vocal | 6 | [Deploiement Docker Local des Services GenAI](../../MyIA.AI.Notebooks/GenAI/00-GenAI-Environment/00-6-Local-Docker-Deployment.ipynb) | BETA | Non | | 7 | [GenAI Environment — Terminal pour les longs…](../../MyIA.AI.Notebooks/GenAI/00-GenAI-Environment/00-7-Terminal-Long-Runs.ipynb) | BETA | Non | +## GenAI/3D (1 notebooks) + +| # | Notebook | Maturité | Exécutable | +|---|----------|----------|------------| +| 1 | [3D-01 — NeRF from scratch : représenter une scène 3D…](../../MyIA.AI.Notebooks/GenAI/3D/3D-01-NeRF-From-Scratch.ipynb) | ALPHA | Non | + ## GenAI/Audio (37 notebooks) | # | Notebook | Maturité | Exécutable | @@ -158,7 +164,7 @@ Génération d'images (DALL-E, Stable Diffusion, Qwen, ComfyUI), synthèse vocal | 7 | [Aspire : le routeur MultiConnector — vetting en ligne,…](../../MyIA.AI.Notebooks/GenAI/Integrations-DotNet/Aspire/07-Aspire-SemanticFleet-MultiConnector.ipynb) | BETA | Non | | 8 | [Aspire : l'asynchrone aux frontieres natives -…](../../MyIA.AI.Notebooks/GenAI/Integrations-DotNet/Aspire/08-Aspire-AsyncFFI-Dotnet.ipynb) | BETA | Oui | | 9 | [Aspire : le harness Copilot SDK — CopilotClient,…](../../MyIA.AI.Notebooks/GenAI/Integrations-DotNet/Aspire/09-Aspire-Harness-CopilotSdk.ipynb) | BETA | Oui | -| 10 | [GitHub Copilot SDK en C# : binding, streaming, Scrutor](../../MyIA.AI.Notebooks/GenAI/Integrations-DotNet/CopilotSDK/01-GitHub-Copilot-SDK-Binding.ipynb) | ALPHA | Non | +| 10 | [GitHub Copilot SDK en C# : binding, streaming, Scrutor](../../MyIA.AI.Notebooks/GenAI/Integrations-DotNet/CopilotSDK/01-GitHub-Copilot-SDK-Binding.ipynb) | BETA | Non | | 11 | [EF Core : des requêtes vérifiées à la compilation](../../MyIA.AI.Notebooks/GenAI/Integrations-DotNet/EFCore/01-EFCore-Requetes-Compilees.ipynb) | BETA | Oui | | 12 | [Orleans × Aspire : le silo orchestré, les identités…](../../MyIA.AI.Notebooks/GenAI/Integrations-DotNet/Orleans/02-Orleans-Aspire-CoHost.ipynb) | BETA | Oui | | 13 | [Orleans × Aspire : un cluster de deux silos, l'état…](../../MyIA.AI.Notebooks/GenAI/Integrations-DotNet/Orleans/04-Orleans-Aspire-Cluster-Redis.ipynb) | BETA | Non | diff --git a/docs/curriculum/ia-symbolique.md b/docs/curriculum/ia-symbolique.md index b753b0d2a6..e4c546f18f 100644 --- a/docs/curriculum/ia-symbolique.md +++ b/docs/curriculum/ia-symbolique.md @@ -20,9 +20,9 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | Métrique | Valeur | |----------|--------| -| Notebooks | 314 | +| Notebooks | 321 | | PRODUCTION | 0 | -| BETA | 305 | +| BETA | 312 | | ALPHA | 9 | ## SymbolicAI (1 notebooks) @@ -67,7 +67,7 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | 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 (86 notebooks) +## SymbolicAI/Lean (93 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -75,88 +75,95 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | 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 | [Lean 17a — Conway, les Nœuds et la Preuve de Piccirillo](../../MyIA.AI.Notebooks/SymbolicAI/Lean/KNOTS/KNOTS-01-Conway-Proofs-Lean-Python.ipynb) | BETA | Non | -| 11 | [Lean 17b — Invariants de Nœuds : Calcul et Vérification](../../MyIA.AI.Notebooks/SymbolicAI/Lean/KNOTS/KNOTS-02-Invariants-Python.ipynb) | BETA | Non | -| 12 | [Lean 17c — Le lake knot_lean par ses déclarations…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/KNOTS/KNOTS-03-Companion-Formel-Lean-Python.ipynb) | BETA | Non | -| 13 | [Langlands 01 : formes modulaires — de SL₂(ℤ) aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Langlands/01-formes-modulaires-sl2z-hecke.ipynb) | BETA | Non | -| 14 | [Monstrous Moonshine : l'invariant $j$ et le monstre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Langlands/02-monstrous-moonshine-invariant-j.ipynb) | BETA | Non | -| 15 | [Lean 4 - Installation et Configuration](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-01-Setup-Lean-Python.ipynb) | BETA | Non | -| 16 | [Lean 2 - Types Dependants et Calcul des Constructions](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-02-Dependent-Types-Lean.ipynb) | BETA | Non | -| 17 | [Lean 3 - Propositions et Preuves](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-03-Propositions-Proofs-Lean.ipynb) | BETA | Non | -| 18 | [Lean-3b — Formalized Formal Logic : le laboratoire…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-03b-Formalized-Formal-Logic-Lean-Python.ipynb) | BETA | Non | -| 19 | [Lean 4 - Quantificateurs et Logique du Premier Ordre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-04-Quantifiers-Lean.ipynb) | BETA | Non | -| 20 | [Lean 5 - Mode Tactique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-05-Tactics-Lean.ipynb) | BETA | Non | -| 21 | [Lean 6 - Mathlib4 : La Bibliotheque Mathematique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-06-Mathlib-Essentials-Lean.ipynb) | BETA | Non | -| 22 | [Lean 7 - Integration des LLMs pour l'Assistance aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-07-LLM-Integration-Lean-Python.ipynb) | BETA | Non | -| 23 | [Lean 7b - Exemples Progressifs et Benchmarks](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-07b-Examples-Python.ipynb) | BETA | Non | -| 24 | [Lean-8 - Agents Autonomes pour Demonstration de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-08-Agentic-Proving-Python.ipynb) | BETA | Non | -| 25 | [Lean 8b : le programme Erdős et le pattern…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-08b-Erdos-Formal-Conjectures-Lean.ipynb) | BETA | Non | -| 26 | [Lean 9 : Multi-Agents avec Semantic Kernel](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-09-SK-Multi-Agents-Lean-Python.ipynb) | BETA | Non | -| 27 | [Lean 10 : LeanDojo - ML/LLM Theorem Proving](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-10-LeanDojo.ipynb) | BETA | Non | -| 28 | [Lean-10b — LeanDojo-v2 : du tracage a la recherche de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-10b-LeanDojo-v2-Pantograph-Lean-Python.ipynb) | BETA | Non | -| 29 | [Lean 11 - TorchLean : Réseaux de Neurones Formellement…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-11-TorchLean.ipynb) | BETA | Non | -| 30 | [Lean 11b - TorchLean : Implémentation Python des…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-11b-TorchLean-Python.ipynb) | BETA | Non | -| 31 | [Lean-12 : Le Théorème de Sensibilité (Huang 2019)](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12-Sensitivity-Theorem.ipynb) | BETA | Non | -| 32 | [Lean-12b — Théorème de Sensibilité de Huang (companion…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12b-Lean-Sensitivity-Theorem.ipynb) | BETA | Non | -| 33 | [Lean-12c : algèbre TPR — binding, unbinding et…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12c-Tensor-Product-Representations-Lean.ipynb) | BETA | Non | -| 34 | [Lean-13 : Le Théorème de Kochen-Specker (Cabello 18…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13-Kochen-Specker.ipynb) | BETA | Non | -| 35 | [Lean-13b : la borne de Tsirelson — digestion formelle…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13b-CHSH-Tsirelson-Native.ipynb) | BETA | Non | -| 36 | [Lean-13c : la saturation de Tsirelson — le témoin de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13c-CHSH-Landau-Saturation.ipynb) | BETA | Non | -| 37 | [Lean-13d : du CHSH au libre arbitre — la route…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13d-CHSH-Indeterminisme-Native.ipynb) | BETA | Non | -| 38 | [Lean-15 : Hommage a Alexandre Grothendieck -- Le…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15-Grothendieck-Tribute.ipynb) | BETA | Non | -| 39 | [Lean-15b : Grothendieck en Lean -- Atelier pratique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15b-Lean-Grothendieck.ipynb) | BETA | Non | -| 40 | [Lean-15d : Grothendieck en images](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15d-Lean-Grothendieck-Visuel-Python.ipynb) | ALPHA | Non | -| 41 | [Lean-16a - Conway, l'homme et l'oeuvre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16a-Conway-Man-and-Work.ipynb) | BETA | Non | -| 42 | [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 | -| 43 | [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 | -| 44 | [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 | -| 45 | [Lean-16e : FRACTRAN, la machine universelle de Conway,…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16e-Conway-FRACTRAN-Lean-Native.ipynb) | BETA | Non | -| 46 | [Lean-16f : Le Théorème du Libre Arbitre (Conway-Kochen)](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16f-Conway-Free-Will-Theorem.ipynb) | BETA | Non | -| 47 | [Lean 16g — Canons : le barreau 2 de l'échelle des…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16g-Conway-Canons.ipynb) | BETA | Non | -| 48 | [Lean-16h : la tournée des motifs du Jeu de la Vie —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16h-Conway-PatternTour-Native.ipynb) | BETA | Non | -| 49 | [Lean-16i — Synthèse d'un translateur minuscule :…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16i-Translateur-Life.ipynb) | BETA | Non | -| 50 | [Lean-16j : la preuve de correction Hashlife — compagnon…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16j-Conway-Hashlife-Correctness-Native.ipynb) | BETA | Non | -| 51 | [Lean-20 : Capstone — digérer le travail formel de Tao…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-20-Capstone-Digestions-Tao-Python.ipynb) | BETA | Non | -| 52 | [Lean-21 : Detection MIMO par flips -- le seuil 2 log N…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21-MIMO-Detection-Flips.ipynb) | BETA | Non | -| 53 | [Lean-21b : le lake mimo_lean par ses énoncés —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21b-MIMO-Converse-Native.ipynb) | BETA | Non | -| 54 | [Lean-21c : Le budget de descente - quand la…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21c-Descente-Budget.ipynb) | BETA | Non | -| 55 | [Lean-22 : Le problème inverse de Galois — M₂₃ refermé…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-22-Galois-Probleme-Inverse-M23.ipynb) | BETA | Non | -| 56 | [Lean-23 : ERC-20 sous Lean 4 — l'invariant de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-23-ERC20-Invariant-Companion.ipynb) | BETA | Non | -| 57 | [Lean-23b — ERC-20 natif : l'invariant de conservation…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-23b-Lean-ERC20-Native-Companion.ipynb) | BETA | Non | -| 58 | [Lean-24 : le lake calibration_lean par ses énoncés —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-24-Calibration-Native-Companion.ipynb) | BETA | Non | -| 59 | [Lean-24b : Confiance et preuves — quand un certificat…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-24b-Confiance-Preuves-Native.ipynb) | BETA | Non | -| 60 | [Lean-25 — Cohérence et témoin : de Finetti construit le…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-25-Coherence-et-Temoin.ipynb) | BETA | Non | -| 61 | [Lean-26 : Hommage à James R. Munkres — le cours 18.901…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-26-Munkres-Tribute.ipynb) | BETA | Non | -| 62 | [Lean-27 : coloration d'arêtes et conjecture de Tutte —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-27-EdgeColoring-Tutte-Companion.ipynb) | BETA | Non | -| 63 | [Lean-28 : Le problème de Hopf sur S⁶ — digestion d'une…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-28-Complex-Structure-S6.ipynb) | BETA | Non | -| 64 | [Lean-29 : les opérateurs de Hecke $T_p$ et $U_p$ —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-29-Hecke-Operators-Native.ipynb) | BETA | Non | -| 65 | [Lean-30 : groupes formels multivariés — compagnon natif](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-30-FormalGroups-Native.ipynb) | BETA | Non | -| 66 | [Lean-31 : Euler et Navier–Stokes — reproduction pinée,…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-31-Euler-Navier-Stokes.ipynb) | BETA | Non | -| 67 | [Lean-33 : espaces de Schwartz — décroissance et…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-33-Distribution-Spaces.ipynb) | BETA | Non | -| 68 | [Lean-34 — Calculabilité et limites : de l'arrêt aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-34-Calculabilite-et-Limites.ipynb) | BETA | Non | -| 69 | [Lean-34b — FairBot par le théorème de Löb : coopérer…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-34b-FairBot-Loeb.ipynb) | BETA | Non | -| 70 | [Lean-36 : structures mathematiques finies — l'Annexe A…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-36-Structures-Finies-MUH-Lean.ipynb) | BETA | Non | -| 71 | [Lean-37 : Capstone — la sous-série « Serre 100 »](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-37-Capstone-Serre100.ipynb) | BETA | Non | -| 72 | [Corps finis et la borne de Hasse — distiller un…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/01-corps-finis-borne-hasse.ipynb) | BETA | Non | -| 73 | [2. Valeurs zêta multiples finies — l'anneau des adèles…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/02-valeurs-zeta-multiples-finies.ipynb) | BETA | Non | -| 74 | [Cohomologie de Čech calculée — espaces topologiques…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/03-cohomologie-cech-espaces-finis.ipynb) | BETA | Non | -| 75 | [Lemme de Yoneda calculé — catégories finies](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/04-lemme-yoneda-categories-finies.ipynb) | BETA | Non | -| 76 | [5. Tables de caractères — le squelette combinatoire…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/05-table-de-caracteres.ipynb) | BETA | Non | -| 77 | [Les bulles diaboliques de Minkowski — géométrie des…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/06-bulles-minkowski.ipynb) | BETA | Non | -| 78 | [Zéros de fonctions L, gaps et statistique GUE](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/07-zeros-fonctions-l-gaps-gue.ipynb) | BETA | Non | -| 79 | [Serre dans Mathlib — tour guidé des cinq monuments](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/08-serre-dans-mathlib-Lean.ipynb) | BETA | Non | -| 80 | [τ de Ramanujan — congruences, borne de Deligne, et la…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/09-congruences-tau-lacunarite-delta.ipynb) | BETA | Non | -| 81 | [10 — Empilements de sphères : la borne linéaire de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/10-empilements-borne-lp-cohn-elkies.ipynb) | BETA | Non | -| 82 | [11 — Corps quadratiques imaginaires, caractères de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/11-corps-quadratiques-reciprocite-quadratique.ipynb) | BETA | Non | -| 83 | [12 - Formes quadratiques binaires et nombre de classes](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/12-formes-quadratiques-binaires-nombre-classes.ipynb) | BETA | Non | -| 84 | [13 - Loi de reciprocité quadratique II : symbole de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/13-jacobi-kronecker-reciprocite-II.ipynb) | BETA | Non | -| 85 | [14 - Composition des formes quadratiques binaires et…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/14-formes-quadratiques-composition-gauss.ipynb) | BETA | Non | -| 86 | [15 - Théorème de Lagrange : tout entier est somme de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/15-quatre-carres-lagrange.ipynb) | BETA | Non | +| 5 | [ANALYSE-05 : La conjecture KLS démontrée — digérer…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-05-KLS-Lean-Python.ipynb) | BETA | Non | +| 6 | [ANALYSE-08 : Ramsey et van der Waerden — l'énumération…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-08-Ramsey-VdW.ipynb) | BETA | Non | +| 7 | [ANALYSE-09 : Un carreau de ℤ³ qui pave sans périodicité…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-09-Tuilage-Aperiodique.ipynb) | BETA | Non | +| 8 | [ANALYSE-09: A single tile of Z^3 that tiles without…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/ANALYSE/ANALYSE-09-Tuilage-Aperiodique_en.ipynb) | BETA | Non | +| 9 | [Geometry 01 — De la figure à l'équation](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-01-From-Figure-To-Equation.ipynb) | BETA | Non | +| 10 | [Geometry 02 — Prouver par l'algèbre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-02-From-Equation-To-Proof.ipynb) | BETA | Non | +| 11 | [Geometry 03 — La méthode de Wu](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-03-Wu-Method-Python.ipynb) | BETA | Non | +| 12 | [Geometry 03b — Décomposition de Ritt et composantes…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-03b-Ritt-Decomposition-Python.ipynb) | BETA | Non | +| 13 | [Geometry 04 — Raisonner comme un géomètre (DD + AR)](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-04-DD-AR-Python.ipynb) | BETA | Non | +| 14 | [Geometry 05 — Prouvé par Gröbner, prouvé par le noyau](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Geometry/Geometry-05-Pont-Formel-Python.ipynb) | BETA | Non | +| 15 | [Lean 17a — Conway, les Nœuds et la Preuve de Piccirillo](../../MyIA.AI.Notebooks/SymbolicAI/Lean/KNOTS/KNOTS-01-Conway-Proofs-Lean-Python.ipynb) | BETA | Non | +| 16 | [Lean 17b — Invariants de Nœuds : Calcul et Vérification](../../MyIA.AI.Notebooks/SymbolicAI/Lean/KNOTS/KNOTS-02-Invariants-Python.ipynb) | BETA | Non | +| 17 | [Lean 17c — Le lake knot_lean par ses déclarations…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/KNOTS/KNOTS-03-Companion-Formel-Lean-Python.ipynb) | BETA | Non | +| 18 | [Langlands 01 : formes modulaires — de SL₂(ℤ) aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Langlands/01-formes-modulaires-sl2z-hecke.ipynb) | BETA | Non | +| 19 | [Monstrous Moonshine : l'invariant $j$ et le monstre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Langlands/02-monstrous-moonshine-invariant-j.ipynb) | BETA | Non | +| 20 | [Lean 4 - Installation et Configuration](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-01-Setup-Lean-Python.ipynb) | BETA | Non | +| 21 | [Lean 2 - Types Dependants et Calcul des Constructions](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-02-Dependent-Types-Lean.ipynb) | BETA | Non | +| 22 | [Lean 3 - Propositions et Preuves](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-03-Propositions-Proofs-Lean.ipynb) | BETA | Non | +| 23 | [Lean-3b — Formalized Formal Logic : le laboratoire…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-03b-Formalized-Formal-Logic-Lean-Python.ipynb) | BETA | Non | +| 24 | [Lean 4 - Quantificateurs et Logique du Premier Ordre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-04-Quantifiers-Lean.ipynb) | BETA | Non | +| 25 | [Lean 5 - Mode Tactique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-05-Tactics-Lean.ipynb) | BETA | Non | +| 26 | [Lean 6 - Mathlib4 : La Bibliotheque Mathematique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-06-Mathlib-Essentials-Lean.ipynb) | BETA | Non | +| 27 | [Lean 7 - Integration des LLMs pour l'Assistance aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-07-LLM-Integration-Lean-Python.ipynb) | BETA | Non | +| 28 | [Lean 7b - Exemples Progressifs et Benchmarks](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-07b-Examples-Python.ipynb) | BETA | Non | +| 29 | [Lean-8 - Agents Autonomes pour Demonstration de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-08-Agentic-Proving-Python.ipynb) | BETA | Non | +| 30 | [Lean 8b : le programme Erdős et le pattern…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-08b-Erdos-Formal-Conjectures-Lean.ipynb) | BETA | Non | +| 31 | [Lean 9 : Multi-Agents avec Semantic Kernel](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-09-SK-Multi-Agents-Lean-Python.ipynb) | BETA | Non | +| 32 | [Lean 10 : LeanDojo - ML/LLM Theorem Proving](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-10-LeanDojo.ipynb) | BETA | Non | +| 33 | [Lean-10b — LeanDojo-v2 : du tracage a la recherche de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-10b-LeanDojo-v2-Pantograph-Lean-Python.ipynb) | BETA | Non | +| 34 | [Lean 11 - TorchLean : Réseaux de Neurones Formellement…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-11-TorchLean.ipynb) | BETA | Non | +| 35 | [Lean 11b - TorchLean : Implémentation Python des…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-11b-TorchLean-Python.ipynb) | BETA | Non | +| 36 | [Lean-12 : Le Théorème de Sensibilité (Huang 2019)](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12-Sensitivity-Theorem.ipynb) | BETA | Non | +| 37 | [Lean-12b — Théorème de Sensibilité de Huang (companion…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12b-Lean-Sensitivity-Theorem.ipynb) | BETA | Non | +| 38 | [Lean-12c : algèbre TPR — binding, unbinding et…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-12c-Tensor-Product-Representations-Lean.ipynb) | BETA | Non | +| 39 | [Lean-13 : Le Théorème de Kochen-Specker (Cabello 18…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13-Kochen-Specker.ipynb) | BETA | Non | +| 40 | [Lean-13b : la borne de Tsirelson — digestion formelle…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13b-CHSH-Tsirelson-Native.ipynb) | BETA | Non | +| 41 | [Lean-13c : la saturation de Tsirelson — le témoin de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13c-CHSH-Landau-Saturation.ipynb) | BETA | Non | +| 42 | [Lean-13d : du CHSH au libre arbitre — la route…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-13d-CHSH-Indeterminisme-Native.ipynb) | BETA | Non | +| 43 | [Lean-15 : Hommage a Alexandre Grothendieck -- Le…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15-Grothendieck-Tribute.ipynb) | BETA | Non | +| 44 | [Lean-15b : Grothendieck en Lean -- Atelier pratique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15b-Lean-Grothendieck.ipynb) | BETA | Non | +| 45 | [Lean-15d : Grothendieck en images](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-15d-Lean-Grothendieck-Visuel-Python.ipynb) | ALPHA | Non | +| 46 | [Lean-16a - Conway, l'homme et l'oeuvre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16a-Conway-Man-and-Work.ipynb) | BETA | Non | +| 47 | [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 | +| 48 | [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 | +| 49 | [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 | +| 50 | [Lean-16e : FRACTRAN, la machine universelle de Conway,…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16e-Conway-FRACTRAN-Lean-Native.ipynb) | BETA | Non | +| 51 | [Lean-16f : Le Théorème du Libre Arbitre (Conway-Kochen)](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16f-Conway-Free-Will-Theorem.ipynb) | BETA | Non | +| 52 | [Lean 16g — Canons : le barreau 2 de l'échelle des…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16g-Conway-Canons.ipynb) | BETA | Non | +| 53 | [Lean-16h : la tournée des motifs du Jeu de la Vie —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16h-Conway-PatternTour-Native.ipynb) | BETA | Non | +| 54 | [Lean-16i — Synthèse d'un translateur minuscule :…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16i-Translateur-Life.ipynb) | BETA | Non | +| 55 | [Lean-16j : la preuve de correction Hashlife — compagnon…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-16j-Conway-Hashlife-Correctness-Native.ipynb) | BETA | Non | +| 56 | [Lean-17 : le pont Conway — du Game of Life (16) à la…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-17-Conway-Bridge-to-Knots-Python.ipynb) | BETA | Non | +| 57 | [Lean-20 : Capstone — digérer le travail formel de Tao…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-20-Capstone-Digestions-Tao-Python.ipynb) | BETA | Non | +| 58 | [Lean-21 : Detection MIMO par flips -- le seuil 2 log N…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21-MIMO-Detection-Flips.ipynb) | BETA | Non | +| 59 | [Lean-21b : le lake mimo_lean par ses énoncés —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21b-MIMO-Converse-Native.ipynb) | BETA | Non | +| 60 | [Lean-21c : Le budget de descente - quand la…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-21c-Descente-Budget.ipynb) | BETA | Non | +| 61 | [Lean-22 : Le problème inverse de Galois — M₂₃ refermé…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-22-Galois-Probleme-Inverse-M23.ipynb) | BETA | Non | +| 62 | [Lean-23 : ERC-20 sous Lean 4 — l'invariant de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-23-ERC20-Invariant-Companion.ipynb) | BETA | Non | +| 63 | [Lean-23b — ERC-20 natif : l'invariant de conservation…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-23b-Lean-ERC20-Native-Companion.ipynb) | BETA | Non | +| 64 | [Lean-24 : le lake calibration_lean par ses énoncés —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-24-Calibration-Native-Companion.ipynb) | BETA | Non | +| 65 | [Lean-24b : Confiance et preuves — quand un certificat…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-24b-Confiance-Preuves-Native.ipynb) | BETA | Non | +| 66 | [Lean-25 — Cohérence et témoin : de Finetti construit le…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-25-Coherence-et-Temoin.ipynb) | BETA | Non | +| 67 | [Lean-26 : Hommage à James R. Munkres — le cours 18.901…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-26-Munkres-Tribute.ipynb) | BETA | Non | +| 68 | [Lean-27 : coloration d'arêtes et conjecture de Tutte —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-27-EdgeColoring-Tutte-Companion.ipynb) | BETA | Non | +| 69 | [Lean-28 : Le problème de Hopf sur S⁶ — digestion d'une…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-28-Complex-Structure-S6.ipynb) | BETA | Non | +| 70 | [Lean-29 : les opérateurs de Hecke $T_p$ et $U_p$ —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-29-Hecke-Operators-Native.ipynb) | BETA | Non | +| 71 | [Lean-30 : groupes formels multivariés — compagnon natif](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-30-FormalGroups-Native.ipynb) | BETA | Non | +| 72 | [Lean-31 : Euler et Navier–Stokes — reproduction pinée,…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-31-Euler-Navier-Stokes.ipynb) | BETA | Non | +| 73 | [Lean-33 : espaces de Schwartz — décroissance et…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-33-Distribution-Spaces.ipynb) | BETA | Non | +| 74 | [Lean-34 — Calculabilité et limites : de l'arrêt aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-34-Calculabilite-et-Limites.ipynb) | BETA | Non | +| 75 | [Lean-34b — FairBot par le théorème de Löb : coopérer…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-34b-FairBot-Loeb.ipynb) | BETA | Non | +| 76 | [Lean-36 : structures mathematiques finies — l'Annexe A…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-36-Structures-Finies-MUH-Lean.ipynb) | BETA | Non | +| 77 | [Lean-37 : Capstone — la sous-série « Serre 100 »](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-37-Capstone-Serre100.ipynb) | BETA | Non | +| 78 | [Capstone Geometry — l'escalier d'entrée : de la figure…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-38-Capstone-Geometry-Lean-Python.ipynb) | BETA | Non | +| 79 | [Corps finis et la borne de Hasse — distiller un…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/01-corps-finis-borne-hasse.ipynb) | BETA | Non | +| 80 | [2. Valeurs zêta multiples finies — l'anneau des adèles…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/02-valeurs-zeta-multiples-finies.ipynb) | BETA | Non | +| 81 | [Cohomologie de Čech calculée — espaces topologiques…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/03-cohomologie-cech-espaces-finis.ipynb) | BETA | Non | +| 82 | [Lemme de Yoneda calculé — catégories finies](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/04-lemme-yoneda-categories-finies.ipynb) | BETA | Non | +| 83 | [5. Tables de caractères — le squelette combinatoire…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/05-table-de-caracteres.ipynb) | BETA | Non | +| 84 | [Les bulles diaboliques de Minkowski — géométrie des…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/06-bulles-minkowski.ipynb) | BETA | Non | +| 85 | [Zéros de fonctions L, gaps et statistique GUE](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/07-zeros-fonctions-l-gaps-gue.ipynb) | BETA | Non | +| 86 | [Serre dans Mathlib — tour guidé des cinq monuments](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/08-serre-dans-mathlib-Lean.ipynb) | BETA | Non | +| 87 | [τ de Ramanujan — congruences, borne de Deligne, et la…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/09-congruences-tau-lacunarite-delta.ipynb) | BETA | Non | +| 88 | [10 — Empilements de sphères : la borne linéaire de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/10-empilements-borne-lp-cohn-elkies.ipynb) | BETA | Non | +| 89 | [11 — Corps quadratiques imaginaires, caractères de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/11-corps-quadratiques-reciprocite-quadratique.ipynb) | BETA | Non | +| 90 | [12 - Formes quadratiques binaires et nombre de classes](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/12-formes-quadratiques-binaires-nombre-classes.ipynb) | BETA | Non | +| 91 | [13 - Loi de reciprocité quadratique II : symbole de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/13-jacobi-kronecker-reciprocite-II.ipynb) | BETA | Non | +| 92 | [14 - Composition des formes quadratiques binaires et…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/14-formes-quadratiques-composition-gauss.ipynb) | BETA | Non | +| 93 | [15 - Théorème de Lagrange : tout entier est somme de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Serre100/15-quatre-carres-lagrange.ipynb) | BETA | Non | ## SymbolicAI/Planners (25 notebooks) diff --git a/docs/curriculum/recherche.md b/docs/curriculum/recherche.md index fd7b9817d9..c2df34177b 100644 --- a/docs/curriculum/recherche.md +++ b/docs/curriculum/recherche.md @@ -20,12 +20,12 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | Métrique | Valeur | |----------|--------| -| Notebooks | 298 | +| Notebooks | 305 | | PRODUCTION | 0 | -| BETA | 286 | -| ALPHA | 12 | +| BETA | 291 | +| ALPHA | 14 | -## GameTheory (95 notebooks) +## GameTheory (96 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -91,41 +91,42 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | 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 | Non | -| 91 | [GameTheory-19 : L'abstraction a dette mesurable](../../MyIA.AI.Notebooks/GameTheory/GameTheory-19-Abstraction-a-Dette-Python.ipynb) | BETA | Oui | -| 92 | [GameTheory 24b : Le temoin d'impossibilite](../../MyIA.AI.Notebooks/GameTheory/GameTheory-20b-Chemin-Minimal-Temoins-Impossibilite-Python.ipynb) | BETA | Oui | -| 93 | [GameTheory 20c : Le chemin minimal sur un second…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-20c-Chemin-Minimal-3x2-Ordinal-Python.ipynb) | BETA | Oui | -| 94 | [GameTheory-21 — Loi II, seconde jambe : synthétiser un…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-20d-Loi-II-Translateur-Life-Python.ipynb) | BETA | Oui | -| 95 | [GameTheory-20e -- Perplexite structurelle Hashlife :…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-20e-Perplexite-Structurelle-Hashlife-Python.ipynb) | BETA | Oui | +| 63 | [GameTheory-13e : Réviser un modèle d'adversaire --…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13e-Revision-Croyances-Adversaire-Python.ipynb) | BETA | Oui | +| 64 | [GameTheory-14 : Jeux Differentiels et Equilibres de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames-CSharp.ipynb) | BETA | Oui | +| 65 | [GameTheory-14 : Jeux Differentiels et Equilibres de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames-Python.ipynb) | BETA | Oui | +| 66 | [GameTheory-15 — Jeux Coopératifs (Twin C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames-CSharp.ipynb) | BETA | Oui | +| 67 | [GameTheory-15-CooperativeGames-Python](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames-Python.ipynb) | BETA | Oui | +| 68 | [GameTheory 15b - Jeux Cooperatifs en Lean :…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15b-Lean-CooperativeGames-Lean.ipynb) | BETA | Non | +| 69 | [GameTheory 15c - Jeux Cooperatifs (C# / .NET)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-CSharp.ipynb) | BETA | Oui | +| 70 | [GameTheory 15c - Jeux Cooperatifs Lean (Python)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-Python.ipynb) | BETA | Oui | +| 71 | [GameTheory 15d - La decomposition de Mobius sur le…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15d-Mobius-Coalitions-Lean-Python.ipynb) | BETA | Non | +| 72 | [GameTheory-15e — Pouvoir coalitionnel : calcul, SMT…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15e-Coalition-Power-SMT-Python.ipynb) | BETA | Oui | +| 73 | [GameTheory 15f - Valeur de Shapley de groupe : évaluer…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15f-Shapley-Groupes-Python.ipynb) | BETA | Oui | +| 74 | [GameTheory 15g - Assistance Games (résultat 2026)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15g-AssistanceGames-2026-Python.ipynb) | BETA | Oui | +| 75 | [GameTheory-16-MechanismDesign-Python (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign-CSharp.ipynb) | BETA | Oui | +| 76 | [GameTheory-16 : Théorie des Mécanismes et Principe de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign-Python.ipynb) | BETA | Oui | +| 77 | [GameTheory-16b : Automated Mechanism Design (AMD)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16b-Automated-Mechanism-Design-Python.ipynb) | BETA | Oui | +| 78 | [GameTheory-16c : La dimension paiement que le designer…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16c-Extraction-de-Revenu-DSIC-IR-Python.ipynb) | BETA | Oui | +| 79 | [GameTheory-16d — L'echange de reins : de la valeur…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16d-Echange-de-Reins-Lean-Python.ipynb) | BETA | Non | +| 80 | [GameTheory-16e : Pilote — joueurs LLM hétérogènes sur…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16e-LLM-Players-Othman-Sandholm-Python.ipynb) | BETA | Non | +| 81 | [GameTheory 23b — Le lake assignment_lean par son…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16f-Lean-Assignment-Lean.ipynb) | BETA | Non | +| 82 | [GameTheory-23 — L'algorithme de Kuhn-Munkres :…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16f-Munkres-Assignment-Python.ipynb) | BETA | Oui | +| 83 | [GameTheory-17 (C#) : Multi-Agent Reinforcement Learning…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL-CSharp.ipynb) | BETA | Oui | +| 84 | [GameTheory-17 : Apprentissage par Renforcement…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL-Python.ipynb) | BETA | Oui | +| 85 | [Information asymétrique : types privés, antisélection…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17b-Asymmetric-Information-Python.ipynb) | BETA | Oui | +| 86 | [Le marché des lemons : le certificat formel exécuté](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17c-Lean-Lemons-Certificat-Lean.ipynb) | BETA | Non | +| 87 | [Screening, signal et anticipation : les trois réponses…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17d-Lean-Screening-Signaling-Lean.ipynb) | BETA | Non | +| 88 | [Du marché au bilan : le pont théorie des jeux théorie…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17f-Market-to-Balance-Sheet-Python.ipynb) | BETA | Oui | +| 89 | [GameTheory-18 : Open Games et Lentilles -- la…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18-Open-Games-et-Lentilles-Python.ipynb) | BETA | Oui | +| 90 | [GameTheory-18b : Casser la composition — où la…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18b-Casser-la-Composition-Python.ipynb) | BETA | Oui | +| 91 | [GameTheory-24 : Banc de calibration — humour, forme…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18c-Humour-Banc-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 | +| 96 | [GameTheory-20e -- Perplexite structurelle Hashlife :…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-20e-Perplexite-Structurelle-Hashlife-Python.ipynb) | BETA | Oui | -## GameTheory/SocialChoice (11 notebooks) +## GameTheory/SocialChoice (12 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -140,6 +141,7 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | 9 | [SocialChoice-06 : Mobius sur le treillis des coalitions…](../../MyIA.AI.Notebooks/GameTheory/SocialChoice/06-Mobius-Aggregation-Pouvoir-Manipulation.ipynb) | BETA | Oui | | 10 | [07 - Élections de comité par approbation : le core…](../../MyIA.AI.Notebooks/GameTheory/SocialChoice/07-Committees-Core.ipynb) | BETA | Oui | | 11 | [SocialChoice 08 - Kemeny, Ranked Pairs et Dodgson :…](../../MyIA.AI.Notebooks/GameTheory/SocialChoice/08-Kemeny-RankedPairs-Dodgson.ipynb) | ALPHA | Oui | +| 12 | [09 - Comites multi-vainqueurs : STV, Monroe et…](../../MyIA.AI.Notebooks/GameTheory/SocialChoice/09-Committees-STV-Monroe-ChamberlinCourant.ipynb) | BETA | Oui | ## IIT (6 notebooks) @@ -152,7 +154,7 @@ 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 (76 notebooks) +## IIT/ICT-Series (79 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -197,41 +199,44 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | 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 | -| 42 | [ICT-23 — PersonaCatastrophe : la fronce de Thom…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-23-PersonaCatastrophe-Python.ipynb) | BETA | Oui | -| 43 | [ICT-24 — WorkspaceIgnition : l'axe Global Workspace et…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-24-WorkspaceIgnition-Python.ipynb) | BETA | Non | -| 44 | [ICT-25 — InoculationRL : GRPO à récompense *hackable*,…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-25-InoculationRL-Python.ipynb) | BETA | Non | -| 45 | [ICT-26 — Convention de signalisation (expérience A,…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-26-SignalingConvention-Python.ipynb) | BETA | Oui | -| 46 | [ICT-27 — Invention de symboles (expérience B, strate 7)](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-27-SymbolInvention-Python.ipynb) | BETA | Oui | -| 47 | [ICT-28 — Adoption collective et seuil de performativité…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-28-CollectiveAdoption-Python.ipynb) | BETA | Oui | -| 48 | [ICT-30 — Invention inhibée (expérience E, strate 7)](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-30-InhibitedInvention-Python.ipynb) | BETA | Oui | -| 49 | [ICT-31 — Le contraste mesuré à trois substrats :…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-31-ContrasteTroisSubstrats-Python.ipynb) | BETA | Oui | -| 50 | [ICT-32 — Stratification causale du Jeu de la Vie :…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-32-StratificationCausaleLife-Python.ipynb) | BETA | Oui | -| 51 | [ICT-33 — Ensembles ouverts : soupes, collisions, et la…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-33-SoupCollisions-Python.ipynb) | BETA | Oui | -| 52 | [ICT-34 — Le banc de recollement des lectures : quatre…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-34-BancRecollementLectures-Python.ipynb) | BETA | Oui | -| 53 | [ICT-35 -- HumorCausalProbe-Pilot : substrat HLS, sans…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35-HumorCausalProbe-Pilot-Python.ipynb) | BETA | Non | -| 54 | [ICT-35b -- HumorCausalPairs-SAE : paires minimales,…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35b-HumorCausalPairs-SAE-Python.ipynb) | BETA | Non | -| 55 | [ICT-35c -- HumorDepthProfile-SAE : le verdict survit-il…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35c-HumorDepthProfile-SAE-Python.ipynb) | BETA | Oui | -| 56 | [ICT-35d -- HumorTypologyBreakdown-SAE : le verdict…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35d-HumorTypologyBreakdown-SAE-Python.ipynb) | BETA | Non | -| 57 | [ICT-36 — F-Lens : mode factored-geometry, sous-espaces…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-36-FLens-FactoredGeometry-Python.ipynb) | BETA | Oui | -| 58 | [ICT-38 — S-Lens : la représentation porte-t-elle la…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-38-SLens-SelfLocation-Python.ipynb) | BETA | Non | -| 59 | [ICT-39 — Composition de regards](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-39-CompositionRegards-Python.ipynb) | BETA | Oui | -| 60 | [ICT-40b — Cognition analogique : les ondes cérébrales…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-40b-AnalogCognitionWaves-Python.ipynb) | BETA | Non | -| 61 | [Geometrie des features SAE : galaxy, atome, dense --…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-41-SAE-GeometrieFeatures-Python.ipynb) | BETA | Oui | -| 62 | [ICT-41b — Crosscoder : diffuser deux modèles, distilled…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-41b-Crosscoder-Distillation-Python.ipynb) | BETA | Non | -| 63 | [ICT-22c — La géométrie de la vérité : une direction dans…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-22c-GeometryOfTruth-Python.ipynb) | BETA | Non | +| 42 | [ICT-22c — La géométrie de la vérité : une direction…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-22c-GeometryOfTruth-Python.ipynb) | BETA | Non | +| 43 | [ICT-23 — PersonaCatastrophe : la fronce de Thom…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-23-PersonaCatastrophe-Python.ipynb) | BETA | Oui | +| 44 | [ICT-24 — WorkspaceIgnition : l'axe Global Workspace et…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-24-WorkspaceIgnition-Python.ipynb) | BETA | Non | +| 45 | [ICT-25 — InoculationRL : GRPO à récompense *hackable*,…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-25-InoculationRL-Python.ipynb) | BETA | Non | +| 46 | [ICT-26 — Convention de signalisation (expérience A,…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-26-SignalingConvention-Python.ipynb) | BETA | Oui | +| 47 | [ICT-27 — Invention de symboles (expérience B, strate 7)](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-27-SymbolInvention-Python.ipynb) | BETA | Oui | +| 48 | [ICT-28 — Adoption collective et seuil de performativité…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-28-CollectiveAdoption-Python.ipynb) | BETA | Oui | +| 49 | [ICT-30 — Invention inhibée (expérience E, strate 7)](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-30-InhibitedInvention-Python.ipynb) | BETA | Oui | +| 50 | [ICT-31 — Le contraste mesuré à trois substrats :…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-31-ContrasteTroisSubstrats-Python.ipynb) | BETA | Oui | +| 51 | [ICT-32 — Stratification causale du Jeu de la Vie :…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-32-StratificationCausaleLife-Python.ipynb) | BETA | Oui | +| 52 | [ICT-33 — Ensembles ouverts : soupes, collisions, et la…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-33-SoupCollisions-Python.ipynb) | BETA | Oui | +| 53 | [ICT-34 — Le banc de recollement des lectures : quatre…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-34-BancRecollementLectures-Python.ipynb) | BETA | Oui | +| 54 | [ICT-35 -- HumorCausalProbe-Pilot : substrat HLS, sans…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35-HumorCausalProbe-Pilot-Python.ipynb) | BETA | Non | +| 55 | [ICT-35b -- HumorCausalPairs-SAE : paires minimales,…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35b-HumorCausalPairs-SAE-Python.ipynb) | BETA | Non | +| 56 | [ICT-35c -- HumorDepthProfile-SAE : le verdict survit-il…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35c-HumorDepthProfile-SAE-Python.ipynb) | BETA | Oui | +| 57 | [ICT-35d -- HumorTypologyBreakdown-SAE : le verdict…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-35d-HumorTypologyBreakdown-SAE-Python.ipynb) | BETA | Non | +| 58 | [ICT-36 — F-Lens : mode factored-geometry, sous-espaces…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-36-FLens-FactoredGeometry-Python.ipynb) | BETA | Oui | +| 59 | [ICT-38 — S-Lens : la représentation porte-t-elle la…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-38-SLens-SelfLocation-Python.ipynb) | BETA | Non | +| 60 | [ICT-39 — Composition de regards](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-39-CompositionRegards-Python.ipynb) | BETA | Oui | +| 61 | [ICT-40b — Cognition analogique : les ondes cérébrales…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-40b-AnalogCognitionWaves-Python.ipynb) | BETA | Non | +| 62 | [Geometrie des features SAE : galaxy, atome, dense --…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-41-SAE-GeometrieFeatures-Python.ipynb) | BETA | Oui | +| 63 | [ICT-41b — Crosscoder : diffuser deux modèles, distilled…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-41b-Crosscoder-Distillation-Python.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-47 — L'axe douleur : une direction linéaire dans…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-47-PainAxisDistillation-Python.ipynb) | BETA | Non | -| 66 | [ICT — Annexe : la contextualité du zoo de proxys est un…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Annexe-ProxyContextuality.ipynb) | BETA | Oui | -| 67 | [ICT — Substrat argumentation : trajectoires de croyance…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-BeliefTrajectories.ipynb) | BETA | Oui | -| 68 | [Argumentation strate 6 — Acceptabilité QBF :…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-QBFAcceptance.ipynb) | BETA | Oui | -| 69 | [ICT — Substrat argumentation : maintenance de la…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-TruthMaintenance.ipynb) | BETA | Oui | -| 70 | [Boucle auto-referentielle p_hat (case 2 / Epic #9533)](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-PhatSelfReference.ipynb) | BETA | Oui | -| 71 | [ICT -- Dissociation saillance / pregnance (case s ⟂ π)](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-SaillancePregnance.ipynb) | BETA | Oui | -| 72 | [ICT-Greffe4 — Le vote argumenté sur chaîne : fermer la…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Greffe4-VoteOnChain.ipynb) | BETA | Oui | -| 73 | [ICT-Life — Substrat de calibration certifié : le Jeu de…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Life-SubstratCertifie.ipynb) | BETA | Oui | -| 74 | [ICT-MUH — Le texte où Tegmark cite Schmidhuber :…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-MUH-FibreTegmark.ipynb) | BETA | Oui | -| 75 | [Tete-a-tete SAE <-> J-space -- les deux lentilles du…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-SAE-JLens-TeteATete.ipynb) | BETA | Non | -| 76 | [ICT-Synthèse — un seul appareil de mesure, cinq…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Synthese-CrossSubstrat.ipynb) | BETA | Non | +| 66 | [ICT-48 — Onset/SAE Qwen3.5-9B-Base, agregat 4 graines…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-48-Onset9B-Aggregate-Python.ipynb) | ALPHA | Oui | +| 67 | [ICT-48 -- Origami Wolfram pli 2 : 4 classes vs…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-48-WolframClasses-ThermoSignature-Python.ipynb) | BETA | Oui | +| 68 | [ICT — Annexe : la contextualité du zoo de proxys est un…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Annexe-ProxyContextuality.ipynb) | BETA | Oui | +| 69 | [ICT — Substrat argumentation : trajectoires de croyance…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-BeliefTrajectories.ipynb) | BETA | Oui | +| 70 | [Argumentation strate 6 — Acceptabilité QBF :…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-QBFAcceptance.ipynb) | BETA | Oui | +| 71 | [ICT — Substrat argumentation : maintenance de la…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Argumentation-TruthMaintenance.ipynb) | BETA | Oui | +| 72 | [ICT -- Dissociation F2 Dehaene : le self-model…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-DehaeneF2-SelfReport.ipynb) | BETA | Oui | +| 73 | [Boucle auto-referentielle p_hat (case 2 / Epic #9533)](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-PhatSelfReference.ipynb) | BETA | Oui | +| 74 | [ICT -- Dissociation saillance / pregnance (case s ⟂ π)](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Dissociation-SaillancePregnance.ipynb) | BETA | Oui | +| 75 | [ICT-Greffe4 — Le vote argumenté sur chaîne : fermer la…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Greffe4-VoteOnChain.ipynb) | BETA | Oui | +| 76 | [ICT-Life — Substrat de calibration certifié : le Jeu de…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Life-SubstratCertifie.ipynb) | BETA | Oui | +| 77 | [ICT-MUH — Le texte où Tegmark cite Schmidhuber :…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-MUH-FibreTegmark.ipynb) | BETA | Oui | +| 78 | [Tete-a-tete SAE <-> J-space -- les deux lentilles du…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-SAE-JLens-TeteATete.ipynb) | BETA | Non | +| 79 | [ICT-Synthèse — un seul appareil de mesure, cinq…](../../MyIA.AI.Notebooks/IIT/ICT-Series/ICT-Synthese-CrossSubstrat.ipynb) | BETA | Non | ## Probas (1 notebooks) @@ -239,16 +244,17 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté |---|----------|----------|------------| | 1 | [Probas-KLS-Concentration : gap spectral, constante de…](../../MyIA.AI.Notebooks/Probas/Probas-KLS-Concentration.ipynb) | BETA | Oui | -## Probas/Applications (4 notebooks) +## Probas/Applications (5 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| | 1 | [Percolation supercritique : le géant au-dessus du seuil](../../MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-01-Supercritique-Python.ipynb) | ALPHA | Oui | | 2 | [Percolation-02-Lean — le noyau fini de percolation,…](../../MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-02-Lean.ipynb) | BETA | 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 | +| 3 | [Percolation au point critique : exposants finis et loi…](../../MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-03-Critique-Python.ipynb) | BETA | Oui | +| 4 | [Le Framework Rational Speech Act (RSA)](../../MyIA.AI.Notebooks/Probas/Applications/Pyro_RSA_Hyperbole.ipynb) | BETA | Oui | +| 5 | [Quotients, fibres et recollement : ce qui survit à la…](../../MyIA.AI.Notebooks/Probas/Applications/Quotients-Fibres-Recollement-Python.ipynb) | BETA | Oui | -## Probas/DecisionTheory (32 notebooks) +## Probas/DecisionTheory (33 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -257,33 +263,34 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | 3 | [Actuariat-03 — Crédibilité actuarielle de…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Actuariat/Actuariat-03-Actuarial-Credibility.ipynb) | BETA | Oui | | 4 | [Actuariat-04 : Ruine et capital — le processus de…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Actuariat/Actuariat-04-Ruine-Lundberg.ipynb) | BETA | Oui | | 5 | [Actuariat-05 — Valeur de l'Information en Souscription](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Actuariat/Actuariat-05-Valeur-Info-Souscription.ipynb) | BETA | Oui | -| 6 | [Du graphe causal au do-calculus — le pont entre les…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-01-Do-Calculus.ipynb) | BETA | Oui | -| 7 | [CausalBridges-02 — Exiger un estimand :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-02-Dowhy-Estimand-Intervention.ipynb) | BETA | Oui | -| 8 | [CausalBridges-03 — Le contrefactuel individuel : quand…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-03-Dowhy-Contrefactuel-Individuel.ipynb) | BETA | Oui | -| 9 | [CausalBridges-04 — La découverte de structure : le…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-04-Dowhy-Decouverte-Structure.ipynb) | BETA | Oui | -| 10 | [CausalBridges-05 — Le confondeur non observé :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-05-Dowhy-Sensibilite-Confounder.ipynb) | BETA | Oui | -| 11 | [CausalBridges-06 — L'instrument faible : quand le…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-06-Dowhy-Instrument-Faible.ipynb) | BETA | Oui | -| 12 | [Méthodes quasi-expérimentales — identifier l'effet…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-07-Quasi-Experimental.ipynb) | BETA | Oui | -| 13 | [Causal-Fairness — Décomposer la discrimination :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-08-Causal-Fairness.ipynb) | BETA | Oui | -| 14 | [DecInfer-01-Utility-Foundations : Axiomes et Fondements](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-01-Utility-Foundations.ipynb) | BETA | Oui | -| 15 | [DecInfer-02-Théorème de représentation de von…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-02-Lean-ExpectedUtility.ipynb) | BETA | Oui | -| 16 | [DecInfer-02b-Lean-Coherence : Dutch Book et bornes de…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-02b-Lean-Coherence.ipynb) | BETA | Oui | -| 17 | [DecInfer-03-Utility-Money : Utilite de l'Argent et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-03-Utility-Money.ipynb) | BETA | Oui | -| 18 | [DecInfer-04-Multi-Attribute : Utilite Multi-Attributs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-04-Multi-Attribute.ipynb) | BETA | Oui | -| 19 | [DecInfer-05-Decision-Networks : Reseaux de Decision](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-05-Decision-Networks.ipynb) | BETA | Oui | -| 20 | [DecInfer-06-Value-Information : Valeur de l'Information](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-06-Value-Information.ipynb) | BETA | Oui | -| 21 | [DecInfer-07-Expert-Systems : Decisions Robustes et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-07-Expert-Systems.ipynb) | BETA | Oui | -| 22 | [DecInfer-08-Sequential : MDPs, Bandits et POMDPs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-08-Sequential.ipynb) | BETA | Oui | -| 23 | [DecInfer-08b-Preuves formelles — Indice de Gittins](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-08b-Lean-Gittins.ipynb) | BETA | Oui | -| 24 | [DecInfer-10-Thompson-Sampling : Bandits bayesiens par…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-10-Thompson-Sampling.ipynb) | BETA | Oui | -| 25 | [DecPyMC-08 : Capstone — la sous-série Actuariat](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-08-Actuariat-Capstone.ipynb) | BETA | Oui | -| 26 | [DecPyMC-1-Utility-Foundations : Axiomes et Fondements](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-1-Utility-Foundations.ipynb) | BETA | Oui | -| 27 | [DecPyMC-2-Utility-Money : Utilite de l'Argent et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-2-Utility-Money.ipynb) | BETA | Oui | -| 28 | [DecPyMC-3-Multi-Attribute : Utilite Multi-Attributs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-3-Multi-Attribute.ipynb) | BETA | Oui | -| 29 | [DecPyMC-4-Decision-Networks : Reseaux de Decision](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-4-Decision-Networks.ipynb) | BETA | Oui | -| 30 | [DecPyMC-5-Valeur de l'Information](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-5-Value-Information.ipynb) | ALPHA | Oui | -| 31 | [DecPyMC-6-Systèmes Experts et Decisions Robustes](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-6-Expert-Systems.ipynb) | BETA | Oui | -| 32 | [DecPyMC-7-MDPs, Bandits et POMDPs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-7-Sequential.ipynb) | BETA | Oui | +| 6 | [CausalBridges-00 — Du graphe causal a l'echelle de…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-00-PearlLadder-Intro-Python.ipynb) | ALPHA | Oui | +| 7 | [Du graphe causal au do-calculus — le pont entre les…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-01-Do-Calculus.ipynb) | BETA | Oui | +| 8 | [CausalBridges-02 — Exiger un estimand :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-02-Dowhy-Estimand-Intervention.ipynb) | BETA | Oui | +| 9 | [CausalBridges-03 — Le contrefactuel individuel : quand…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-03-Dowhy-Contrefactuel-Individuel.ipynb) | BETA | Oui | +| 10 | [CausalBridges-04 — La découverte de structure : le…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-04-Dowhy-Decouverte-Structure.ipynb) | BETA | Oui | +| 11 | [CausalBridges-05 — Le confondeur non observé :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-05-Dowhy-Sensibilite-Confounder.ipynb) | BETA | Oui | +| 12 | [CausalBridges-06 — L'instrument faible : quand le…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-06-Dowhy-Instrument-Faible.ipynb) | BETA | Oui | +| 13 | [Méthodes quasi-expérimentales — identifier l'effet…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-07-Quasi-Experimental.ipynb) | BETA | Oui | +| 14 | [Causal-Fairness — Décomposer la discrimination :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-08-Causal-Fairness.ipynb) | BETA | Oui | +| 15 | [DecInfer-01-Utility-Foundations : Axiomes et Fondements](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-01-Utility-Foundations.ipynb) | BETA | Oui | +| 16 | [DecInfer-02-Théorème de représentation de von…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-02-Lean-ExpectedUtility.ipynb) | BETA | Oui | +| 17 | [DecInfer-02b-Lean-Coherence : Dutch Book et bornes de…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-02b-Lean-Coherence.ipynb) | BETA | Oui | +| 18 | [DecInfer-03-Utility-Money : Utilite de l'Argent et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-03-Utility-Money.ipynb) | BETA | Oui | +| 19 | [DecInfer-04-Multi-Attribute : Utilite Multi-Attributs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-04-Multi-Attribute.ipynb) | BETA | Oui | +| 20 | [DecInfer-05-Decision-Networks : Reseaux de Decision](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-05-Decision-Networks.ipynb) | BETA | Oui | +| 21 | [DecInfer-06-Value-Information : Valeur de l'Information](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-06-Value-Information.ipynb) | BETA | Oui | +| 22 | [DecInfer-07-Expert-Systems : Decisions Robustes et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-07-Expert-Systems.ipynb) | BETA | Oui | +| 23 | [DecInfer-08-Sequential : MDPs, Bandits et POMDPs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-08-Sequential.ipynb) | BETA | Oui | +| 24 | [DecInfer-08b-Preuves formelles — Indice de Gittins](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-08b-Lean-Gittins.ipynb) | BETA | Oui | +| 25 | [DecInfer-10-Thompson-Sampling : Bandits bayesiens par…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-10-Thompson-Sampling.ipynb) | BETA | Oui | +| 26 | [DecPyMC-08 : Capstone — la sous-série Actuariat](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-08-Actuariat-Capstone.ipynb) | BETA | Oui | +| 27 | [DecPyMC-1-Utility-Foundations : Axiomes et Fondements](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-1-Utility-Foundations.ipynb) | BETA | Oui | +| 28 | [DecPyMC-2-Utility-Money : Utilite de l'Argent et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-2-Utility-Money.ipynb) | BETA | Oui | +| 29 | [DecPyMC-3-Multi-Attribute : Utilite Multi-Attributs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-3-Multi-Attribute.ipynb) | BETA | Oui | +| 30 | [DecPyMC-4-Decision-Networks : Reseaux de Decision](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-4-Decision-Networks.ipynb) | BETA | Oui | +| 31 | [DecPyMC-5-Valeur de l'Information](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-5-Value-Information.ipynb) | ALPHA | Oui | +| 32 | [DecPyMC-6-Systèmes Experts et Decisions Robustes](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-6-Expert-Systems.ipynb) | BETA | Oui | +| 33 | [DecPyMC-7-MDPs, Bandits et POMDPs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-7-Sequential.ipynb) | BETA | Oui | ## Probas/Infer (21 notebooks) diff --git a/docs/curriculum/trading.md b/docs/curriculum/trading.md index 281a5ff0c8..5e277aaab3 100644 --- a/docs/curriculum/trading.md +++ b/docs/curriculum/trading.md @@ -20,144 +20,150 @@ Stratégies de trading algorithmique avec QuantConnect, pipeline ML (Transformer | Métrique | Valeur | |----------|--------| -| Notebooks | 283 | +| Notebooks | 291 | | PRODUCTION | 0 | -| BETA | 262 | -| ALPHA | 21 | +| BETA | 269 | +| ALPHA | 22 | -## ML/DataScienceWithAgents (102 notebooks) +## ML/DataScienceWithAgents (108 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| -| 1 | [1.2 - Manipulation de Données avec NumPy](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.2-Manipulation_de_Donnees_avec_NumPy.ipynb) | BETA | Oui | -| 2 | [1.3 - Analyse de Données avec Pandas](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.3-Analyse_de_Donnees_avec_Pandas.ipynb) | BETA | Oui | -| 3 | [2.1 — Le workflow d'apprentissage automatique](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.1-Workflow-ML.ipynb) | BETA | Oui | -| 4 | [2.10 — Optimisation d'hyperparamètres : grille, hasard,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.10-Optimisation-Hyperparametres.ipynb) | BETA | Non | -| 5 | [2.11 — Régularisation sparse : LASSO (L1) vs Ridge…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11-Regularisation-Sparse-LASSO.ipynb) | BETA | Oui | -| 6 | [2.11b — Operateurs proximaux : ISTA et FISTA from…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11b-Proximal-Operators-From-Scratch.ipynb) | BETA | Oui | -| 7 | [2.11c — Lasso SOTA : coordinate descent, LassoCV, et…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11c-Lasso-SOTA-Comparison.ipynb) | ALPHA | Oui | -| 8 | [2.11d — ADMM from scratch](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11d-Optimisation-ADMM-From-Scratch.ipynb) | ALPHA | Oui | -| 9 | [2.11f — Comparaison bloc A / bloc B : le tableau croisé…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11f-Comparaison-Optimisation-Convexe.ipynb) | BETA | Oui | -| 10 | [2.12 — Données déséquilibrées : la courbe PR, les…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.12-Donnees-Desequilibrees.ipynb) | BETA | Oui | -| 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 | [2.15 — 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 | [2.4b — AdaBoost *from scratch* : booster des apprenants…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.4b-AdaBoost-From-Scratch.ipynb) | BETA | Oui | -| 22 | [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 | -| 23 | [2.5b — Calibration des probabilités : reliability…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5b-Calibration-Probabilites.ipynb) | BETA | Oui | -| 24 | [2.5c — Equite par sous-groupe : compromis…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5c-Equite-Sous-Groupes.ipynb) | BETA | Oui | -| 25 | [2.5d — Dérive de distribution au déploiement :…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5d-Derive-Distribution-Deploiement.ipynb) | ALPHA | Oui | -| 26 | [2.6 — Clustering (KMeans) et réduction de dimension…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.6-Clustering-KMeans-PCA.ipynb) | BETA | Oui | -| 27 | [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 | -| 28 | [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 | -| 29 | [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 | -| 30 | [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 | -| 31 | [2.8c — Borne + Témoin extrémal + Concentration : ce que…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8c-Borne-Temoin-Concentration.ipynb) | BETA | Oui | -| 32 | [Novikoff : la convergence du perceptron, démontrée et…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8d-Lean-Novikoff-Convergence.ipynb) | BETA | Oui | -| 33 | [2.9 — Grokking : la généralisation qui arrive en retard](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9-Grokking-Generalisation.ipynb) | BETA | Oui | -| 34 | [2.9b — GenEFT : une théorie effective de la…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9b-GenEFT-Theorie-Effective.ipynb) | BETA | Oui | -| 35 | [2.9c — Grokking : le diagramme de phases](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9c-Grokking-Diagrammes-Phases.ipynb) | BETA | Oui | -| 36 | [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 | -| 37 | [2.9e — MIPS : du réseau au programme](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9e-MIPS-Extraction-Programme.ipynb) | BETA | Non | -| 38 | [3.0 — Théorie de l'information : entropie, KL,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.0-Theorie-Information.ipynb) | BETA | Oui | -| 39 | [3.1 — La rétropropagation : la chaîne des gradients à…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.1-Retropropagation.ipynb) | BETA | Oui | -| 40 | [3.10 — Le pendant SOTA : la bibliothèque diffusers…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.10-Modeles-Generatifs-Diffusion-SOTA.ipynb) | BETA | Non | -| 41 | [3.11 — Le budget mémoire d'un entraînement : quatre…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.11-Budget-Memoire-Entrainement.ipynb) | BETA | Non | -| 42 | [3.12 — Les collectives : l'anneau à la main contre…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.12-Les-Collectives.ipynb) | BETA | Non | -| 43 | [3.2 — Les optimisateurs : de SGD à Adam, ce qui change…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.2-Optimisateurs.ipynb) | BETA | Oui | -| 44 | [3.3 — Régularisation : dropout, weight decay, early…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.3-Regularisation.ipynb) | BETA | Oui | -| 45 | [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 | -| 46 | [3.4c — Mixture of Experts : router les jetons, croître…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4c-MoE-from-scratch.ipynb) | BETA | Non | -| 47 | [3.4d — Fourier features et biais spectral : quand le…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4d-Fourier-Features-Biais-Spectral-Python.ipynb) | ALPHA | Oui | -| 48 | [3.5 — Grokking et double descente : quand la…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.5-Phenomenes-de-Generalisation.ipynb) | BETA | Oui | -| 49 | [3.6 — Modèles génératifs : trois objectifs, trois…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6-Modeles-Generatifs.ipynb) | BETA | Oui | -| 50 | [3.6b — Modèles génératifs en PyTorch : VAE, GAN et…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6b-Modeles-Generatifs-PyTorch.ipynb) | BETA | Oui | -| 51 | [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 | -| 52 | [3.6e — Génération conditionnelle et *classifier-free…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6e-Modeles-Generatifs-Conditionnels-from-scratch.ipynb) | BETA | Non | -| 53 | [3.7 — Distillation maître-élève : quand le savoir se…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.7-Distillation-Maitre-Eleve.ipynb) | BETA | Oui | -| 54 | [Représentations contrastives modernes — du skip-gram…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.8-Representations-Contrastives.ipynb) | BETA | Oui | -| 55 | [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 | -| 56 | [3.9a — Compression par quantification INT8 : le réseau…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9a-Compression-Quantization-INT8.ipynb) | BETA | Non | -| 57 | [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 | -| 58 | [3.9d — Compression par distillation : transférer le…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9d-Compression-Distillation-from-scratch.ipynb) | BETA | Non | -| 59 | [3.9e — Quantification SOTA : la même INT8, par…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9e-Compression-Quantization-SOTA.ipynb) | BETA | Non | -| 60 | [3.9f — Élagage SOTA : les mêmes masques, par…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9f-Compression-Pruning-SOTA.ipynb) | BETA | Non | -| 61 | [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 | -| 62 | [4.1 — Le neurone convolutif from scratch : kernel…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.1-Conv-NumPy-Torch-Allclose.ipynb) | BETA | Oui | -| 63 | [4.2 — ConvNet profonde : pourquoi les résiduelles](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2-ConvNet-Profonde-Residuelles.ipynb) | BETA | Non | -| 64 | [Le gradient qui s'évanouit, le gradient qui survit :…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2b-Lean-GradientFlow-Vanishing.ipynb) | BETA | Oui | -| 65 | [4.3 — Transfer learning : réutiliser un ResNet18…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.3-TransferLearning-ResNet.ipynb) | BETA | Non | -| 66 | [4.4 — Détection d'objets from scratch : la grille…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.4-Detection-Anchor-From-Scratch.ipynb) | BETA | Non | -| 67 | [4.4b — Détection d'objets anchor-free : le renversement…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.4b-Detection-AnchorFree-From-Scratch.ipynb) | BETA | Non | -| 68 | [4.4c — Détection d'objets from scratch : la Focal Loss](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.4c-Detection-FocalLoss-From-Scratch.ipynb) | BETA | Non | -| 69 | [4.5 — Détection SOTA : fine-tuner torchvision plutôt…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5-Detection-SOTA-Torchvision.ipynb) | BETA | Non | -| 70 | [4.5b — Détection SOTA : YOLO sous ultralytics, la…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5b-Detection-SOTA-Ultralytics.ipynb) | BETA | Non | -| 71 | [4.5c — Bench yolov5nu sur le terrain du 4.4 (chunk 2/3,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5c-YOLOv5-Bench-Ultralytics.ipynb) | BETA | Non | -| 72 | [4.5d — Détection SOTA : un second wrapper, LibreYOLO,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5d-Detection-SOTA-LibreYOLO.ipynb) | BETA | Non | -| 73 | [4.5c — Détection SOTA : YOLO sous ultralytics, scènes…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.6-Detection-Ultralytics-Difficult-Scenes.ipynb) | BETA | Non | -| 74 | [4.6b — Détection SOTA : le renversement — le camouflage…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.6b-Detection-Adversarial-Camouflage.ipynb) | BETA | Non | -| 75 | [4.6c — Du patch collé au vêtement porté : le dazzle…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.6c-Detection-Dazzle-Garment-StyleTransfer.ipynb) | BETA | Non | -| 76 | [WS-00a — Ondelettes 1D *from scratch* : analyse…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00a-Ondelettes-1D-from-scratch.ipynb) | BETA | Oui | -| 77 | [WS-00b — Ondelettes 2D *from scratch* : bandes…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00b-Ondelettes-2D-from-scratch.ipynb) | BETA | Oui | -| 78 | [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 | -| 79 | [WS-01 — Débruitage d'images : du seuillage *from…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-01-Denoising-SOTA.ipynb) | BETA | Oui | -| 80 | [WS-02 — Scattering SOTA : kymatio contre le moteur…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-02-Scattering-SOTA.ipynb) | BETA | Non | -| 81 | [WS-03 — Synthèse : représentation construite vs…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-03-Synthese-Scattering-vs-ResNet.ipynb) | BETA | Oui | -| 82 | [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 | -| 83 | [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 | -| 84 | [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 | -| 85 | [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 | -| 86 | [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 | -| 87 | [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 | -| 88 | [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 | -| 89 | [Lab 8: Introduction au Framework ADK et Multi-Provider](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day4-Foundations/Lab8-ADK-Introduction.ipynb) | BETA | Non | -| 90 | [Lab 9: Premier Agent ADK pour Data Science](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day4-Foundations/Lab9-First-ADK-Agent.ipynb) | BETA | Oui | -| 91 | [Lab 10: Data File Analyzer (DS-STAR Component)](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab10-File-Analyzer.ipynb) | BETA | Oui | -| 92 | [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 | -| 93 | [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 | -| 94 | [Lab 12b : Désignation séquentielle — le contrat C4,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12b-Sequential-Orchestration.ipynb) | BETA | Non | -| 95 | [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 | -| 96 | [Lab 12d : Tracabilite de la consommation — le contrat…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12d-Token-Usage.ipynb) | BETA | Non | -| 97 | [Lab 12e: Persistance d'etat de session - une…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12e-Session-Persistence.ipynb) | BETA | Non | -| 98 | [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 | -| 99 | [Lab 14: Ablation et Raffinement Ciblé (MLE-STAR…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab14-Ablation-Refinement.ipynb) | ALPHA | Oui | -| 100 | [Lab 15: Kaggle Challenge avec MLE-STAR](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab15-Kaggle-Challenge.ipynb) | BETA | Oui | -| 101 | [Lab 16: Data Science Agent avec GCP BigQuery](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day7-Production/Lab16-Data-Science-Agent.ipynb) | ALPHA | Oui | -| 102 | [Lab 17: Projet Final - Pipeline DS-STAR Complet](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day7-Production/Lab17-Final-Project.ipynb) | ALPHA | Oui | +| 1 | [1.1 - Python pour la Data Science](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.1-Python_pour_la_Data_Science.ipynb) | BETA | Oui | +| 2 | [1.2 - Manipulation de Données avec NumPy](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.2-Manipulation_de_Donnees_avec_NumPy.ipynb) | BETA | Oui | +| 3 | [1.3 - Analyse de Données avec Pandas](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.3-Analyse_de_Donnees_avec_Pandas.ipynb) | BETA | Oui | +| 4 | [1.4 - Visualisation : Matplotlib puis Seaborn](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.4-Visualisation_Matplotlib_Seaborn.ipynb) | BETA | Oui | +| 5 | [1.5 - Exploration et nettoyage de données réelles](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.5-Exploration_Nettoyage_Donnees_Reelles.ipynb) | BETA | Oui | +| 6 | [1.6 - Statistiques descriptives](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/01-PythonForDataScience/notebooks/1.6-Statistiques_Descriptives.ipynb) | BETA | Oui | +| 7 | [2.1 — Le workflow d'apprentissage automatique](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.1-Workflow-ML.ipynb) | BETA | Oui | +| 8 | [2.10 — Optimisation d'hyperparamètres : grille, hasard,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.10-Optimisation-Hyperparametres.ipynb) | BETA | Non | +| 9 | [2.11 — Régularisation sparse : LASSO (L1) vs Ridge…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11-Regularisation-Sparse-LASSO.ipynb) | BETA | Oui | +| 10 | [2.11b — Operateurs proximaux : ISTA et FISTA from…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11b-Proximal-Operators-From-Scratch.ipynb) | BETA | Oui | +| 11 | [2.11c — Lasso SOTA : coordinate descent, LassoCV, et…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11c-Lasso-SOTA-Comparison.ipynb) | ALPHA | Oui | +| 12 | [2.11d — ADMM from scratch](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11d-Optimisation-ADMM-From-Scratch.ipynb) | ALPHA | Oui | +| 13 | [2.11f — Comparaison bloc A / bloc B : le tableau croisé…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.11f-Comparaison-Optimisation-Convexe.ipynb) | BETA | Oui | +| 14 | [2.12 — Données déséquilibrées : la courbe PR, les…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.12-Donnees-Desequilibrees.ipynb) | BETA | Oui | +| 15 | [2.13 — Analyse d'erreurs : diagnostiquer un modèle…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.13-Analyse-Erreurs.ipynb) | BETA | Oui | +| 16 | [2.14 — Explicabilité (XAI) : SHAP, LIME et…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.14-Explicabilite-SHAP-LIME-Contrefactuels.ipynb) | BETA | Oui | +| 17 | [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 | +| 18 | [2.15 — La donnée comme responsabilité : inférence…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.15-Donnee-Comme-Responsabilite-Python.ipynb) | BETA | Oui | +| 19 | [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 | +| 20 | [2.3 — Régression linéaire et régression logistique](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3-Regression-lineaire-logistique.ipynb) | BETA | Oui | +| 21 | [Naive Bayes génératif vs régression logistique…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3b-Naive-Bayes-Generatif.ipynb) | BETA | Oui | +| 22 | [Régression en grande dimension — quand p >> n : ridge,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3c-Regression-Grande-Dimension.ipynb) | BETA | Oui | +| 23 | [Modèle gaussien, frontière LDA / QDA](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.3d-Modele-Gaussien-LDA-QDA.ipynb) | BETA | Oui | +| 24 | [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 | +| 25 | [2.4b — AdaBoost *from scratch* : booster des apprenants…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.4b-AdaBoost-From-Scratch.ipynb) | BETA | Oui | +| 26 | [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 | +| 27 | [2.5b — Calibration des probabilités : reliability…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5b-Calibration-Probabilites.ipynb) | BETA | Oui | +| 28 | [2.5c — Equite par sous-groupe : compromis…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5c-Equite-Sous-Groupes.ipynb) | BETA | Oui | +| 29 | [2.5d — Dérive de distribution au déploiement :…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.5d-Derive-Distribution-Deploiement.ipynb) | ALPHA | Oui | +| 30 | [2.6 — Clustering (KMeans) et réduction de dimension…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.6-Clustering-KMeans-PCA.ipynb) | BETA | Oui | +| 31 | [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 | +| 32 | [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 | +| 33 | [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 | +| 34 | [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 | +| 35 | [2.8c — Borne + Témoin extrémal + Concentration : ce que…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8c-Borne-Temoin-Concentration.ipynb) | BETA | Oui | +| 36 | [Novikoff : la convergence du perceptron, démontrée et…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.8d-Lean-Novikoff-Convergence.ipynb) | BETA | Oui | +| 37 | [2.9 — Grokking : la généralisation qui arrive en retard](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9-Grokking-Generalisation.ipynb) | BETA | Oui | +| 38 | [2.9b — GenEFT : une théorie effective de la…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9b-GenEFT-Theorie-Effective.ipynb) | BETA | Oui | +| 39 | [2.9c — Grokking : le diagramme de phases](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9c-Grokking-Diagrammes-Phases.ipynb) | BETA | Oui | +| 40 | [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 | +| 41 | [2.9e — MIPS : du réseau au programme](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9e-MIPS-Extraction-Programme.ipynb) | BETA | Non | +| 42 | [2.9f - Théorie effective du grokking en Lean :…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/02-ML-Cours/2.9f-Grokking-Theorie-Effective-Lean.ipynb) | BETA | Oui | +| 43 | [3.0 — Théorie de l'information : entropie, KL,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.0-Theorie-Information.ipynb) | BETA | Oui | +| 44 | [3.1 — La rétropropagation : la chaîne des gradients à…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.1-Retropropagation.ipynb) | BETA | Oui | +| 45 | [3.10 — Le pendant SOTA : la bibliothèque diffusers…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.10-Modeles-Generatifs-Diffusion-SOTA.ipynb) | BETA | Non | +| 46 | [3.11 — Le budget mémoire d'un entraînement : quatre…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.11-Budget-Memoire-Entrainement.ipynb) | BETA | Non | +| 47 | [3.12 — Les collectives : l'anneau à la main contre…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.12-Les-Collectives.ipynb) | BETA | Non | +| 48 | [3.14 - Debogage d un entrainement qui tourne mais n…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.14-Debug-Entrainement-N-Apprend-Pas-Python.ipynb) | BETA | Oui | +| 49 | [3.2 — Les optimisateurs : de SGD à Adam, ce qui change…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.2-Optimisateurs.ipynb) | BETA | Oui | +| 50 | [3.3 — Régularisation : dropout, weight decay, early…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.3-Regularisation.ipynb) | BETA | Oui | +| 51 | [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 | +| 52 | [3.4c — Mixture of Experts : router les jetons, croître…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4c-MoE-from-scratch.ipynb) | BETA | Non | +| 53 | [3.4d — Fourier features et biais spectral : quand le…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.4d-Fourier-Features-Biais-Spectral-Python.ipynb) | ALPHA | Oui | +| 54 | [3.5 — Grokking et double descente : quand la…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.5-Phenomenes-de-Generalisation.ipynb) | BETA | Oui | +| 55 | [3.6 — Modèles génératifs : trois objectifs, trois…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6-Modeles-Generatifs.ipynb) | BETA | Oui | +| 56 | [3.6b — Modèles génératifs en PyTorch : VAE, GAN et…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6b-Modeles-Generatifs-PyTorch.ipynb) | BETA | Oui | +| 57 | [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 | +| 58 | [3.6e — Génération conditionnelle et *classifier-free…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.6e-Modeles-Generatifs-Conditionnels-from-scratch.ipynb) | BETA | Non | +| 59 | [3.7 — Distillation maître-élève : quand le savoir se…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.7-Distillation-Maitre-Eleve.ipynb) | BETA | Oui | +| 60 | [Représentations contrastives modernes — du skip-gram…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.8-Representations-Contrastives.ipynb) | BETA | Oui | +| 61 | [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 | +| 62 | [3.9a — Compression par quantification INT8 : le réseau…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9a-Compression-Quantization-INT8.ipynb) | BETA | Non | +| 63 | [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 | +| 64 | [3.9d — Compression par distillation : transférer le…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9d-Compression-Distillation-from-scratch.ipynb) | BETA | Non | +| 65 | [3.9e — Quantification SOTA : la même INT8, par…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9e-Compression-Quantization-SOTA.ipynb) | BETA | Non | +| 66 | [3.9f — Élagage SOTA : les mêmes masques, par…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/03-DeepLearning/3.9f-Compression-Pruning-SOTA.ipynb) | BETA | Non | +| 67 | [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 | +| 68 | [4.1 — Le neurone convolutif from scratch : kernel…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.1-Conv-NumPy-Torch-Allclose.ipynb) | BETA | Oui | +| 69 | [4.2 — ConvNet profonde : pourquoi les résiduelles](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2-ConvNet-Profonde-Residuelles.ipynb) | BETA | Non | +| 70 | [Le gradient qui s'évanouit, le gradient qui survit :…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.2b-Lean-GradientFlow-Vanishing.ipynb) | BETA | Oui | +| 71 | [4.3 — Transfer learning : réutiliser un ResNet18…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.3-TransferLearning-ResNet.ipynb) | BETA | Non | +| 72 | [4.4 — Détection d'objets from scratch : la grille…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.4-Detection-Anchor-From-Scratch.ipynb) | BETA | Non | +| 73 | [4.4b — Détection d'objets anchor-free : le renversement…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.4b-Detection-AnchorFree-From-Scratch.ipynb) | BETA | Non | +| 74 | [4.4c — Détection d'objets from scratch : la Focal Loss](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.4c-Detection-FocalLoss-From-Scratch.ipynb) | BETA | Non | +| 75 | [4.5 — Détection SOTA : fine-tuner torchvision plutôt…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5-Detection-SOTA-Torchvision.ipynb) | BETA | Non | +| 76 | [4.5b — Détection SOTA : YOLO sous ultralytics, la…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5b-Detection-SOTA-Ultralytics.ipynb) | BETA | Non | +| 77 | [4.5c — Bench yolov5nu sur le terrain du 4.4 (chunk 2/3,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5c-YOLOv5-Bench-Ultralytics.ipynb) | BETA | Non | +| 78 | [4.5d — Détection SOTA : un second wrapper, LibreYOLO,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.5d-Detection-SOTA-LibreYOLO.ipynb) | BETA | Non | +| 79 | [4.5c — Détection SOTA : YOLO sous ultralytics, scènes…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.6-Detection-Ultralytics-Difficult-Scenes.ipynb) | BETA | Non | +| 80 | [4.6b — Détection SOTA : le renversement — le camouflage…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.6b-Detection-Adversarial-Camouflage.ipynb) | BETA | Non | +| 81 | [4.6c — Du patch collé au vêtement porté : le dazzle…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04-Vision/4.6c-Detection-Dazzle-Garment-StyleTransfer.ipynb) | BETA | Non | +| 82 | [WS-00a — Ondelettes 1D *from scratch* : analyse…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00a-Ondelettes-1D-from-scratch.ipynb) | BETA | Oui | +| 83 | [WS-00b — Ondelettes 2D *from scratch* : bandes…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-00b-Ondelettes-2D-from-scratch.ipynb) | BETA | Oui | +| 84 | [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 | +| 85 | [WS-01 — Débruitage d'images : du seuillage *from…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-01-Denoising-SOTA.ipynb) | BETA | Oui | +| 86 | [WS-02 — Scattering SOTA : kymatio contre le moteur…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-02-Scattering-SOTA.ipynb) | BETA | Non | +| 87 | [WS-03 — Synthèse : représentation construite vs…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/04b-Wavelet-Scattering/WS-03-Synthese-Scattering-vs-ResNet.ipynb) | BETA | Oui | +| 88 | [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 | +| 89 | [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 | +| 90 | [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 | +| 91 | [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 | +| 92 | [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 | +| 93 | [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 | +| 94 | [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 | +| 95 | [Lab 8: Introduction au Framework ADK et Multi-Provider](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day4-Foundations/Lab8-ADK-Introduction.ipynb) | BETA | Non | +| 96 | [Lab 9: Premier Agent ADK pour Data Science](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day4-Foundations/Lab9-First-ADK-Agent.ipynb) | BETA | Oui | +| 97 | [Lab 10: Data File Analyzer (DS-STAR Component)](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab10-File-Analyzer.ipynb) | BETA | Oui | +| 98 | [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 | +| 99 | [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 | +| 100 | [Lab 12b : Désignation séquentielle — le contrat C4,…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12b-Sequential-Orchestration.ipynb) | BETA | Non | +| 101 | [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 | +| 102 | [Lab 12d : Tracabilite de la consommation — le contrat…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12d-Token-Usage.ipynb) | BETA | Non | +| 103 | [Lab 12e: Persistance d'etat de session - une…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day5-DS-Star/Lab12e-Session-Persistence.ipynb) | BETA | Non | +| 104 | [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 | +| 105 | [Lab 14: Ablation et Raffinement Ciblé (MLE-STAR…](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab14-Ablation-Refinement.ipynb) | ALPHA | Oui | +| 106 | [Lab 15: Kaggle Challenge avec MLE-STAR](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day6-MLE-Star/Lab15-Kaggle-Challenge.ipynb) | BETA | Oui | +| 107 | [Lab 16: Data Science Agent avec GCP BigQuery](../../MyIA.AI.Notebooks/ML/DataScienceWithAgents/Track2-GoogleADK/Day7-Production/Lab16-Data-Science-Agent.ipynb) | ALPHA | Oui | +| 108 | [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) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| -| 1 | [ML-1 (Python) : Introduction au Machine Learning avec…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-01-Introduction-Python.ipynb) | BETA | Oui | -| 2 | [ML-1 : Introduction au Machine Learning avec ML.NET](../../MyIA.AI.Notebooks/ML/ML.Net/ML-01-Introduction.ipynb) | BETA | Oui | -| 3 | [ML-10 (Python) : l'illusion de progression en détection…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-09b-TSAD-Benchmark-Flaws-Python.ipynb) | BETA | Oui | -| 4 | [ML-11 : le Matrix Profile multidimensionnel, une…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-09c-MatrixProfile-Multidim-Python.ipynb) | BETA | Oui | -| 5 | [ML-2 : Préparation des données et ingénierie des…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-02-Data%26Features-Python.ipynb) | BETA | Oui | -| 6 | [ML-2 : Préparation des données et ingénierie des…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-02-Data%26Features.ipynb) | BETA | Oui | -| 7 | [ML-3 : Entraînement et AutoML](../../MyIA.AI.Notebooks/ML/ML.Net/ML-03-Entrainement%26AutoML.ipynb) | BETA | Oui | -| 8 | [ML-3 (Python) : Entraînement et AutoML](../../MyIA.AI.Notebooks/ML/ML.Net/ML-03-Entrainement&AutoML-Python.ipynb) | BETA | Oui | -| 9 | [ML-4 : Évaluation des modèles (Python / sklearn)](../../MyIA.AI.Notebooks/ML/ML.Net/ML-04-Evaluation-Python.ipynb) | BETA | Oui | -| 10 | [ML-4 : Evaluation des modèles](../../MyIA.AI.Notebooks/ML/ML.Net/ML-04-Evaluation.ipynb) | BETA | Oui | -| 11 | [ML-4b : Validité statistique des comparaisons de…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-04b-ModelComparison-Validity-Python.ipynb) | BETA | Oui | -| 12 | [ML-5 (Python) : Prévision de séries temporelles (STL +…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-05-TimeSeries-Python.ipynb) | BETA | Oui | -| 13 | [ML-5 : Time Series Forecasting avec ML.NET](../../MyIA.AI.Notebooks/ML/ML.Net/ML-05-TimeSeries.ipynb) | BETA | Oui | -| 14 | [ML-5b (Python) : Séries temporelles classiques —…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-05b-Series-Temporelles-Classiques-Python.ipynb) | BETA | Oui | -| 15 | [ML-6 (Python) : Intégration de modèles ONNX (skl2onnx +…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-06-ONNX-Python.ipynb) | BETA | Oui | -| 16 | [ML-6 : ONNX Model Integration avec ML.NET](../../MyIA.AI.Notebooks/ML/ML.Net/ML-06-ONNX.ipynb) | BETA | Oui | -| 17 | [ML-7 (Python) : Systèmes de recommandation par…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-07-Recommendation-Python.ipynb) | BETA | Oui | -| 18 | [ML-7 : Systèmes de Recommandation avec ML.NET](../../MyIA.AI.Notebooks/ML/ML.Net/ML-07-Recommendation.ipynb) | BETA | Oui | -| 19 | [ML-8 (Python) : Clustering non-supervisé avec K-Means](../../MyIA.AI.Notebooks/ML/ML.Net/ML-08-Clustering-Python.ipynb) | BETA | Oui | -| 20 | [ML-8 : Clustering non-supervise avec K-Means](../../MyIA.AI.Notebooks/ML/ML.Net/ML-08-Clustering.ipynb) | BETA | Oui | -| 21 | [ML-9 (Python) : Détection d'anomalies par PCA (erreur…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-09-Anomaly-Detection-Python.ipynb) | BETA | Oui | -| 22 | [ML-9 : Detection d'anomalies avec Randomized PCA](../../MyIA.AI.Notebooks/ML/ML.Net/ML-09-Anomaly-Detection.ipynb) | BETA | Oui | +| 1 | [ML-01 (Python) : Introduction au Machine Learning avec…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-01-Introduction-Python.ipynb) | BETA | Oui | +| 2 | [ML-01 : Introduction au Machine Learning avec ML.NET](../../MyIA.AI.Notebooks/ML/ML.Net/ML-01-Introduction.ipynb) | BETA | Oui | +| 3 | [ML-02 : Préparation des données et ingénierie des…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-02-Data%26Features-Python.ipynb) | BETA | Oui | +| 4 | [ML-02 : Préparation des données et ingénierie des…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-02-Data%26Features.ipynb) | BETA | Oui | +| 5 | [ML-03 (Python) : Entraînement et AutoML](../../MyIA.AI.Notebooks/ML/ML.Net/ML-03-Entrainement%26AutoML-Python.ipynb) | BETA | Oui | +| 6 | [ML-03 : Entraînement et AutoML](../../MyIA.AI.Notebooks/ML/ML.Net/ML-03-Entrainement%26AutoML.ipynb) | BETA | Oui | +| 7 | [ML-04 : Évaluation des modèles (Python / sklearn)](../../MyIA.AI.Notebooks/ML/ML.Net/ML-04-Evaluation-Python.ipynb) | BETA | Oui | +| 8 | [ML-04 : Evaluation des modèles](../../MyIA.AI.Notebooks/ML/ML.Net/ML-04-Evaluation.ipynb) | BETA | Oui | +| 9 | [ML-04b : Validité statistique des comparaisons de…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-04b-ModelComparison-Validity-Python.ipynb) | BETA | Oui | +| 10 | [ML-05 (Python) : Prévision de séries temporelles (STL +…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-05-TimeSeries-Python.ipynb) | BETA | Oui | +| 11 | [ML-05 : Time Series Forecasting avec ML.NET](../../MyIA.AI.Notebooks/ML/ML.Net/ML-05-TimeSeries.ipynb) | BETA | Oui | +| 12 | [ML-05b (Python) : Séries temporelles classiques —…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-05b-Series-Temporelles-Classiques-Python.ipynb) | BETA | Oui | +| 13 | [ML-06 (Python) : Intégration de modèles ONNX (skl2onnx…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-06-ONNX-Python.ipynb) | BETA | Oui | +| 14 | [ML-06 : ONNX Model Integration avec ML.NET](../../MyIA.AI.Notebooks/ML/ML.Net/ML-06-ONNX.ipynb) | BETA | Oui | +| 15 | [ML-07 (Python) : Systèmes de recommandation par…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-07-Recommendation-Python.ipynb) | BETA | Oui | +| 16 | [ML-07 : Systèmes de Recommandation avec ML.NET](../../MyIA.AI.Notebooks/ML/ML.Net/ML-07-Recommendation.ipynb) | BETA | Oui | +| 17 | [ML-08 (Python) : Clustering non-supervisé avec K-Means](../../MyIA.AI.Notebooks/ML/ML.Net/ML-08-Clustering-Python.ipynb) | BETA | Oui | +| 18 | [ML-08 : Clustering non-supervise avec K-Means](../../MyIA.AI.Notebooks/ML/ML.Net/ML-08-Clustering.ipynb) | BETA | Oui | +| 19 | [ML-09 (Python) : Détection d'anomalies par PCA (erreur…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-09-Anomaly-Detection-Python.ipynb) | BETA | Oui | +| 20 | [ML-09 : Detection d'anomalies avec Randomized PCA](../../MyIA.AI.Notebooks/ML/ML.Net/ML-09-Anomaly-Detection.ipynb) | BETA | Oui | +| 21 | [ML-09b (Python) : l'illusion de progression en…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-09b-TSAD-Benchmark-Flaws-Python.ipynb) | BETA | Oui | +| 22 | [ML-09c : le Matrix Profile multidimensionnel, une…](../../MyIA.AI.Notebooks/ML/ML.Net/ML-09c-MatrixProfile-Multidim-Python.ipynb) | BETA | Oui | | 23 | [TP : Prevision des ventes d'assurance](../../MyIA.AI.Notebooks/ML/ML.Net/TP-prevision-ventes.ipynb) | BETA | Oui | ## Probas (1 notebooks) @@ -166,16 +172,17 @@ Stratégies de trading algorithmique avec QuantConnect, pipeline ML (Transformer |---|----------|----------|------------| | 1 | [Probas-KLS-Concentration : gap spectral, constante de…](../../MyIA.AI.Notebooks/Probas/Probas-KLS-Concentration.ipynb) | BETA | Oui | -## Probas/Applications (4 notebooks) +## Probas/Applications (5 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| | 1 | [Percolation supercritique : le géant au-dessus du seuil](../../MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-01-Supercritique-Python.ipynb) | ALPHA | Oui | | 2 | [Percolation-02-Lean — le noyau fini de percolation,…](../../MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-02-Lean.ipynb) | BETA | 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 | +| 3 | [Percolation au point critique : exposants finis et loi…](../../MyIA.AI.Notebooks/Probas/Applications/Percolation/Percolation-03-Critique-Python.ipynb) | BETA | Oui | +| 4 | [Le Framework Rational Speech Act (RSA)](../../MyIA.AI.Notebooks/Probas/Applications/Pyro_RSA_Hyperbole.ipynb) | BETA | Oui | +| 5 | [Quotients, fibres et recollement : ce qui survit à la…](../../MyIA.AI.Notebooks/Probas/Applications/Quotients-Fibres-Recollement-Python.ipynb) | BETA | Oui | -## Probas/DecisionTheory (32 notebooks) +## Probas/DecisionTheory (33 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -184,33 +191,34 @@ Stratégies de trading algorithmique avec QuantConnect, pipeline ML (Transformer | 3 | [Actuariat-03 — Crédibilité actuarielle de…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Actuariat/Actuariat-03-Actuarial-Credibility.ipynb) | BETA | Oui | | 4 | [Actuariat-04 : Ruine et capital — le processus de…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Actuariat/Actuariat-04-Ruine-Lundberg.ipynb) | BETA | Oui | | 5 | [Actuariat-05 — Valeur de l'Information en Souscription](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Actuariat/Actuariat-05-Valeur-Info-Souscription.ipynb) | BETA | Oui | -| 6 | [Du graphe causal au do-calculus — le pont entre les…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-01-Do-Calculus.ipynb) | BETA | Oui | -| 7 | [CausalBridges-02 — Exiger un estimand :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-02-Dowhy-Estimand-Intervention.ipynb) | BETA | Oui | -| 8 | [CausalBridges-03 — Le contrefactuel individuel : quand…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-03-Dowhy-Contrefactuel-Individuel.ipynb) | BETA | Oui | -| 9 | [CausalBridges-04 — La découverte de structure : le…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-04-Dowhy-Decouverte-Structure.ipynb) | BETA | Oui | -| 10 | [CausalBridges-05 — Le confondeur non observé :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-05-Dowhy-Sensibilite-Confounder.ipynb) | BETA | Oui | -| 11 | [CausalBridges-06 — L'instrument faible : quand le…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-06-Dowhy-Instrument-Faible.ipynb) | BETA | Oui | -| 12 | [Méthodes quasi-expérimentales — identifier l'effet…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-07-Quasi-Experimental.ipynb) | BETA | Oui | -| 13 | [Causal-Fairness — Décomposer la discrimination :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-08-Causal-Fairness.ipynb) | BETA | Oui | -| 14 | [DecInfer-01-Utility-Foundations : Axiomes et Fondements](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-01-Utility-Foundations.ipynb) | BETA | Oui | -| 15 | [DecInfer-02-Théorème de représentation de von…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-02-Lean-ExpectedUtility.ipynb) | BETA | Oui | -| 16 | [DecInfer-02b-Lean-Coherence : Dutch Book et bornes de…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-02b-Lean-Coherence.ipynb) | BETA | Oui | -| 17 | [DecInfer-03-Utility-Money : Utilite de l'Argent et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-03-Utility-Money.ipynb) | BETA | Oui | -| 18 | [DecInfer-04-Multi-Attribute : Utilite Multi-Attributs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-04-Multi-Attribute.ipynb) | BETA | Oui | -| 19 | [DecInfer-05-Decision-Networks : Reseaux de Decision](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-05-Decision-Networks.ipynb) | BETA | Oui | -| 20 | [DecInfer-06-Value-Information : Valeur de l'Information](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-06-Value-Information.ipynb) | BETA | Oui | -| 21 | [DecInfer-07-Expert-Systems : Decisions Robustes et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-07-Expert-Systems.ipynb) | BETA | Oui | -| 22 | [DecInfer-08-Sequential : MDPs, Bandits et POMDPs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-08-Sequential.ipynb) | BETA | Oui | -| 23 | [DecInfer-08b-Preuves formelles — Indice de Gittins](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-08b-Lean-Gittins.ipynb) | BETA | Oui | -| 24 | [DecInfer-10-Thompson-Sampling : Bandits bayesiens par…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-10-Thompson-Sampling.ipynb) | BETA | Oui | -| 25 | [DecPyMC-08 : Capstone — la sous-série Actuariat](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-08-Actuariat-Capstone.ipynb) | BETA | Oui | -| 26 | [DecPyMC-1-Utility-Foundations : Axiomes et Fondements](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-1-Utility-Foundations.ipynb) | BETA | Oui | -| 27 | [DecPyMC-2-Utility-Money : Utilite de l'Argent et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-2-Utility-Money.ipynb) | BETA | Oui | -| 28 | [DecPyMC-3-Multi-Attribute : Utilite Multi-Attributs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-3-Multi-Attribute.ipynb) | BETA | Oui | -| 29 | [DecPyMC-4-Decision-Networks : Reseaux de Decision](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-4-Decision-Networks.ipynb) | BETA | Oui | -| 30 | [DecPyMC-5-Valeur de l'Information](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-5-Value-Information.ipynb) | ALPHA | Oui | -| 31 | [DecPyMC-6-Systèmes Experts et Decisions Robustes](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-6-Expert-Systems.ipynb) | BETA | Oui | -| 32 | [DecPyMC-7-MDPs, Bandits et POMDPs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-7-Sequential.ipynb) | BETA | Oui | +| 6 | [CausalBridges-00 — Du graphe causal a l'echelle de…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-00-PearlLadder-Intro-Python.ipynb) | ALPHA | Oui | +| 7 | [Du graphe causal au do-calculus — le pont entre les…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-01-Do-Calculus.ipynb) | BETA | Oui | +| 8 | [CausalBridges-02 — Exiger un estimand :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-02-Dowhy-Estimand-Intervention.ipynb) | BETA | Oui | +| 9 | [CausalBridges-03 — Le contrefactuel individuel : quand…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-03-Dowhy-Contrefactuel-Individuel.ipynb) | BETA | Oui | +| 10 | [CausalBridges-04 — La découverte de structure : le…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-04-Dowhy-Decouverte-Structure.ipynb) | BETA | Oui | +| 11 | [CausalBridges-05 — Le confondeur non observé :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-05-Dowhy-Sensibilite-Confounder.ipynb) | BETA | Oui | +| 12 | [CausalBridges-06 — L'instrument faible : quand le…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-06-Dowhy-Instrument-Faible.ipynb) | BETA | Oui | +| 13 | [Méthodes quasi-expérimentales — identifier l'effet…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-07-Quasi-Experimental.ipynb) | BETA | Oui | +| 14 | [Causal-Fairness — Décomposer la discrimination :…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/Causal-Bridges/CausalBridges-08-Causal-Fairness.ipynb) | BETA | Oui | +| 15 | [DecInfer-01-Utility-Foundations : Axiomes et Fondements](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-01-Utility-Foundations.ipynb) | BETA | Oui | +| 16 | [DecInfer-02-Théorème de représentation de von…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-02-Lean-ExpectedUtility.ipynb) | BETA | Oui | +| 17 | [DecInfer-02b-Lean-Coherence : Dutch Book et bornes de…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-02b-Lean-Coherence.ipynb) | BETA | Oui | +| 18 | [DecInfer-03-Utility-Money : Utilite de l'Argent et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-03-Utility-Money.ipynb) | BETA | Oui | +| 19 | [DecInfer-04-Multi-Attribute : Utilite Multi-Attributs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-04-Multi-Attribute.ipynb) | BETA | Oui | +| 20 | [DecInfer-05-Decision-Networks : Reseaux de Decision](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-05-Decision-Networks.ipynb) | BETA | Oui | +| 21 | [DecInfer-06-Value-Information : Valeur de l'Information](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-06-Value-Information.ipynb) | BETA | Oui | +| 22 | [DecInfer-07-Expert-Systems : Decisions Robustes et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-07-Expert-Systems.ipynb) | BETA | Oui | +| 23 | [DecInfer-08-Sequential : MDPs, Bandits et POMDPs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-08-Sequential.ipynb) | BETA | Oui | +| 24 | [DecInfer-08b-Preuves formelles — Indice de Gittins](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-08b-Lean-Gittins.ipynb) | BETA | Oui | +| 25 | [DecInfer-10-Thompson-Sampling : Bandits bayesiens par…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecInfer/DecInfer-10-Thompson-Sampling.ipynb) | BETA | Oui | +| 26 | [DecPyMC-08 : Capstone — la sous-série Actuariat](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-08-Actuariat-Capstone.ipynb) | BETA | Oui | +| 27 | [DecPyMC-1-Utility-Foundations : Axiomes et Fondements](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-1-Utility-Foundations.ipynb) | BETA | Oui | +| 28 | [DecPyMC-2-Utility-Money : Utilite de l'Argent et…](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-2-Utility-Money.ipynb) | BETA | Oui | +| 29 | [DecPyMC-3-Multi-Attribute : Utilite Multi-Attributs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-3-Multi-Attribute.ipynb) | BETA | Oui | +| 30 | [DecPyMC-4-Decision-Networks : Reseaux de Decision](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-4-Decision-Networks.ipynb) | BETA | Oui | +| 31 | [DecPyMC-5-Valeur de l'Information](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-5-Value-Information.ipynb) | ALPHA | Oui | +| 32 | [DecPyMC-6-Systèmes Experts et Decisions Robustes](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-6-Expert-Systems.ipynb) | BETA | Oui | +| 33 | [DecPyMC-7-MDPs, Bandits et POMDPs](../../MyIA.AI.Notebooks/Probas/DecisionTheory/DecPyMC/DecPyMC-7-Sequential.ipynb) | BETA | Oui | ## Probas/Infer (21 notebooks)