README
Machine Learning for Trading — 3rd Edition
Build, test, and deploy ML-driven trading strategies — from data sourcing to live execution.
This repository hosts the code for Machine Learning for Trading, 3rd Edition by Stefan Jansen — a ground-up rebuild, organized around one end-to-end workflow: how you define a research idea and develop it iteratively into a strategy you can actually run, and keep running, in a live market.
- Nine case studies illustrate the workflow throughout the 27 chapters of the book, from raw data through features, models, backtests, costs, and risk to deployment.
- Generative AI and autonomous agents are new to this edition and cut across that workflow, bringing retrieval-augmented generation, knowledge graphs, and multi-agent systems to financial research.
- The companion website features 112 primers, 56 agent skills, and six production Python libraries that facilitate substantial parts of the workflow.
🎓 New: Live Courses & Lightning Lessons
For the first time, the third edition comes with a live cohort course, hands-on workshops, and free lightning lessons taught by Stefan on Maven — full schedule on the courses page.
- ▶ Machine Learning for Trading: From Research to Production — the flagship live cohort course: take a research idea all the way to a deployed, monitored strategy, working