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Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2Achievement: YOLO

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hamim23z/README.md

Hello! I'm Hamim Choudhury, a current senior at The City College of New York pursuing a major in Computer Science. 👋

  • ⚡ Previous Systems Engineer Intern at Bloom Energy | Prev SWE at NYC DORIS | Prev Web Dev at NYC DDC.
  • 📚 My tech stack consists of Python, JS/TS, Pandas, Seaborn, Docker, XGBoost and more!
  • 🌱 Currently learning more about Machine Learning (building models and using different libraries/tools).
  • 📫 How to reach me: Email at hamimc232@gmail.com or my LinkedIn at https://www.linkedin.com/in/hamimc/

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  1. Professional_Portfolio Professional_Portfolio Public

    My portfolio website made with JavaScript, React, and Material UI. Hosted on Vercel.

    JavaScript

  2. Ertan-Eats Ertan-Eats Public

    This is a website designed to track where @newyorkturk goes to eat throughout NYC. It displays videos, items he ordered, and the ratings. All data in stored in Supabase and pulled from there.

    JavaScript

  3. PDF-Compression PDF-Compression Public

    Automates PDF compression and linearization using Ghostscript and QPDF for efficient storage and fast web viewing.

    Python

  4. NBA-Championship-Predictor NBA-Championship-Predictor Public

    This is a Machine Learning prediction model that predicts the next 25 NBA Champs based on past championships, finals appearances, and Eastern/Western conference appearances. There will be a part 2 …

    Jupyter Notebook

  5. Personal_PDF_Chatbot Personal_PDF_Chatbot Public

    This is a Python/Langchain/HuggingFace application where users will be able to import multiple PDFs and ask questions about the content of the PDFs. Users will also be given the exact location of w…

    Python

  6. SpaceSync_v1 SpaceSync_v1 Public

    Forked from b-Karthikeya-reddy/Marl-ar-benchmark

    Multi-agent reinforcement learning system that benchmarks collaborative furniture placement in simulated AR rooms using specialized layout, style, and budget agents trained on real IKEA data.

    JavaScript