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daniel-mehta/README.md

👋 Hey, I'm Daniel Mehta

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🧠 About Me

Wilfrid Laurier CS & UX grad · Current Humber AI & ML postgrad student
Former Data Analyst and Database Intern at the Ministry of Education and DPCDSB
Some startup experience at Meter — a VC-backed SF company funded by Sam Altman, Sequoia Capital, and Stripe’s founders

🔍 Currently Exploring

  • 🧠 Local LLMs and practical ML workflows
  • 🤖 Currently Learning Deep Learning, Natural Language Processing, Image Processing and Computer Vision, and GNN/LLM fusion
  • 💸 FinTech and developer productivity
  • ⚽ Sports analytics (especially fantasy football/soccer)
  • 🎮 Hobbyist with game dev in Unreal Engine — released one game on Itch.io and aiming to launch it on Steam soon

📬 Reach Out


Open to roles in ML engineering, data science, or anything exciting in tech.


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  1. CooperLM-354M Public

    A 354M parameter GPT-2 model trained on filtered Wikipedia, BookCorpus, and OpenWebText. Includes 4-bit quantized version for lightweight inference. Built as a toy project to explore end-to-end LLM…

    Jupyter Notebook

  2. FitCheck.AI Public

    👔 FitCheck.AI is your personal AI stylist. Upload outfits for savage critiques, auto-tag your wardrobe, and get smart recommendations - powered by Streamlit, LangChain, MongoDB, and VLMs like CLIP …

    Python

  3. Code-Reviewer Public

    A lightweight, LLM-powered tool for reviewing Python code using DeepSeek-Coder via Ollama. The backend was built in a day, with a Streamlit frontend added later for a clean, local code review exper…

    Python 2

  4. Traffic-Management-Q-Learning Public

    An artificial intelligence model for optimizing traffic flow and managing autonomous vehicles using Q-learning. Implements the BNART heuristic for efficient routing.

    Python

  5. AWS-Sentiment-Analysis-Project Public

    Real-time sentiment analysis web app using AWS Comprehend, built with Flask and deployed on AWS EC2.

    Python

  6. Salary-Predictor Public

    Multi-language salary prediction pipeline using Julia (MLJ), Go, SQL, Python and Bash — trained on Kaggle data with a Go-powered web UI.

    Go 2