Machine Learning For Trading

Machine Learning for Trading is the companion site to the third edition of a book by Stefan Jansen on building systematic trading strategies with machine learning. The book follows a workflow from hypothesis formulation through to production deployment, across 27 chapters in six parts: foundations, features, models, strategy, advanced AI covering reinforcement learning, retrieval augmented generation and agents, and production. The site is aimed at quantitative researchers, data scientists and developers who want runnable material rather than theory alone. It adds nine end to end case studies covering equities, ETFs, crypto, options, futures, forex and commodities, six Python libraries for data acquisition, feature engineering, model diagnostics, event driven backtesting and live trading with broker integrations, and a primer of 112 topics in machine learning, statistics and quantitative finance. A set of 61 agent skills gives coding agents guarded workflows that address lookahead bias, data leakage and multiple testing errors. An Agent Lab section is an AI research environment where agents generate forecasts and analyze signals, and users can create an account and sign in. Live workshops and courses are scheduled, including sessions on coding agent workflows and multi agent forecasting. A free newsletter is hosted on Substack. Prices for the book, courses and workshops are not published on the home page.