A running collection of the books, courses, hands-on practice, and tools I actually use for quantitative finance, deep learning, and working with large datasets. I keep adding to this as I find things worth sharing.
A deep dive into building a regime-aware trading system that uses Hidden Markov Models to classify market conditions and dynamically allocate across a strategy pool — from feature engineering to live paper trading.
A detailed walkthrough of how I built a dynamic and customizable Stocks Screener using Python, Streamlit, and real financial data. This project combines finance and data science principles to empower investment research through factor-based strategies.