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Achievement: Pair ExtraordinaireAchievement: Pull Shark

Achievements

Achievement: Pair ExtraordinaireAchievement: Pull Shark

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mousa-alagha/README.md

Mousa Alagha

LinkedIn Email

AI/ML + Embedded Systems engineer building edge AI, computer vision, and applied ML projects with clean, reproducible code.

What I do

  • Build end-to-end ML systems: data → training → evaluation → deployment
  • Build real-time computer vision pipelines on edge devices (Raspberry Pi / microcontrollers)
  • Optimize models for edge: quantization, latency/FPS profiling, performance tuning
  • Ship practical tools: FastAPI services, simple Streamlit dashboards, and Dockerized demos
  • Integrate hardware + software: cameras, sensors, Firebase, and production-style debugging

Featured projects

Tech (short)

Python • C/C++ • PyTorch • TensorFlow/TFLite • OpenCV • FastAPI • Streamlit • Docker • Linux • Raspberry Pi

Open to

  • AI/ML roles (edge AI, computer vision, applied ML)
  • Freelance/consulting (RAG assistants, vision systems, edge deployments)
  • Collabs on useful open-source tools & datasets

Pinned Loading

  1. RPi-based-Lane-Assist-Autonomous-Car RPi-based-Lane-Assist-Autonomous-Car Public

    This project implements a lane-assist autonomous car using a Raspberry Pi and YOLO for object detection, lane detection, and motor control. The car autonomously navigates and avoids obstacles using…

    Python 3

  2. AI-Powered-Exercise-Recognition-Glove AI-Powered-Exercise-Recognition-Glove Public

    A smart, wearable glove that recognizes and tracks exercise movements using AI, real-time feedback, and an interactive button interface.

    C

  3. Edulytics_Capstone_project Edulytics_Capstone_project Public

    Forked from Capedbitmap/Edulytics

    A web application designed to provide real-time transcription of lectures using OpenAI's Realtime API, store them in Firebase, and offer AI-powered explanations and summaries to students. Includes …

    JavaScript 1

  4. PipelineIQ PipelineIQ Public

    AI-powered semantic search & Q/A for oil & gas PDFs. Hybrid RAG (FAISS + BM25), cited answers, Streamlit UI, admin re-ingest, and TTS.

    Python