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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.

A detailed exploration of ETL and ELT, their differences, evolution, and when to use each approach in modern data engineering.

Common Table Expressions vs Subqueries vs Views vs Temp Tables (Materialized vs Non-Materialized)

How Retrieval-Augmented Generation works under the hood, and a practical walkthrough building a RAG-based LLM Q&A app with LangChain, OpenAI, and Pinecone for a graduate ML course.