Table of Contents

1. Algorithmic Trading and Machine Learning in a Nutshell
2. Data Feed, Backtests, and Forward Testing
3. Optimizing Trading Systems, Metrics, and Automated Reporting
4. Implement Trading Strategies
5. Supervised Learning for Trading Systems
6. Improving Model Capability with Features
7. Advanced Machine Learning Models for Trading
8. AutoML and Low-Code for Trading Strategies
9. Unsupervised Learning Methods for Trading
10. Unsupervised Learning with Pattern Matching
11. Trading Signals from Reports and News
12. Advanced Unsupervised Learning, Anomaly Detection, and Association Rules
Appendix: APIs and Libraries for each chapter