Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python

This book is a comprehensive guide to building and evaluating machine learning models for automated trading strategies.

It covers the entire workflow, from data engineering to model optimization and backtesting.

The author uses real-world examples to demonstrate how to leverage NLP and deep learning techniques to extract tradeable signals from market and alternative data.

With this book, you'll learn how to design, train, and evaluate machine learning algorithms that underpin automated trading strategies, as well as how to assess the signal content of new features using Alphalens and SHAP values.

Whether you're a seasoned trader or just starting out, this book is essential reading for anyone looking to harness the power of machine learning in their trading strategies.