Projects

Deep reinforcement learning framework for dynamic cryptocurrency portfolio optimization comparing value-based (DQN, DDQN) and policy gradient (REINFORCE) agents against classical baselines. DDQN outperforms passive strategies with 190.77% returns on a...

End-to-end deep learning trading system evaluating whether GRU neural networks can generate investable alpha in cryptocurrency markets. Full MLOps pipeline from data ingestion to portfolio construction with rigorous walk-forward validation....

Advanced portfolio optimization framework comparing machine learning (GRU) predictions against traditional mean-variance and market-cap weighted strategies. Features quarterly model rotation, rigorous statistical testing, and production-ready backtesting infrastructure.

Production-grade MLOps framework for training and deploying deep learning time-series models for cryptocurrency price prediction. Features walk-forward validation, multi-objective optimization, and end-to-end CLI workflow.

Production-grade data engineering pipeline for cryptocurrency market intelligence. Automates daily OHLCV data collection, computes 30+ technical indicators, generates trading signals, and maintains a market-cap weighted crypto index with comprehensive error...