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    Azjob21/README.md

    Hey, I'm Ayoub

    CS Student · AI & Backend Developer · Game Dev · UI/UX Designer
    Building things that actually work — from ML models to pixel art games


    About Me

    I'm a Computer Science student at ESI-SBA with a broad builder's mindset. I work across the full stack — from training ML models and building APIs, to designing UIs in Figma and making games in Love2D. I participate actively in hackathons and love turning ideas into shipped products.

    • Focused on AI/ML, backend development, and MLOps
    • Indie game developer using Lua + Love2D with pixel art in Aseprite
    • UI/UX designer with Figma
    • Based in Algeria

    🛠️ Skills

    AI & DataPythonPyTorchXGBoostscikit-learnProphetW&B

    BackendFastAPIJavaKotlinSupabase

    FrontendReactTailwindCSSJavaScript

    Game Dev & DesignLuaLove2DAsepriteFigma


    🏆 Featured Projects

    1st place at MobAI'26 hackathon. Full AI system forecasting demand for 1,129 SKUs and optimizing warehouse storage + picking routes. Built with XGBoost, Prophet, and FastAPI. Deployed on Azure with 12 API endpoints.

    PythonXGBoostProphetFastAPIAzureMLOps


    Kaggle competition entry achieving Val Dice 0.9814 and Val IoU 0.9641 on a boundary-heavy segmentation task. The competition scores 80% on boundary precision — making standard segmentation approaches insufficient. Built a custom boundary-aware loss (BCE + Dice + Gradient + Sobel), trained a U-Net with EfficientNet-B3 encoder at 512×640px, and applied TTA + threshold optimization using the actual competition metric. Converged in ~1 hour on a T4 GPU.

    PyTorchU-NetEfficientNetComputer VisionKaggle


    MLOps project using Isolation Forest to detect at-risk students. Includes experiment tracking with W&B, model versioning, CI/CD with GitHub Actions, and a Flask REST API for real-time predictions.

    Pythonscikit-learnFlaskW&BGitHub ActionsMLOps


    A full-stack productivity web app with a 7-day calendar view, color-coded commitments, priority tracking, and Supabase backend. Also packaged as a desktop app with Electron. Live at v0-life-style.vercel.app.

    ReactTailwindSupabaseViteElectronVercel


    🥈Binary X-ray classification using two independent deep learning strategies, both trained on the same dataset and submitted to the Kaggle leaderboard this one ranked second in the datathoon .


    "Ship it, learn from it, improve it."

    Pinned Loading

    1. mobai26-ai-forecasting-warehouse-optimizationmobai26-ai-forecasting-warehouse-optimizationPublic

      MobAI'26: forecasting + warehouse optimization submission

      HTML

    2. ml_project_anomaly_detection_in_students_interactionsml_project_anomaly_detection_in_students_interactionsPublic

      HTML

    3. masked-xray-challengemasked-xray-challengePublic

      Jupyter Notebook

    4. water_segmentationwater_segmentationPublic

      Jupyter Notebook

    5. alzheimer-mri-cdr-classificationalzheimer-mri-cdr-classificationPublic

      Python