This repository contains the Jupyter Notebook code samples that accompany the Machine Learning for Algorithmic Trading (Second Edition) book published by Packt. It covers how to apply machine learning techniques such as supervised learning, reinforcement learning, and deep learning to build trading strategies, backtest them, and optimize performance. The notebooks demonstrate data sourcing, feature engineering, model training, and strategy evaluation.