This repository provides study notes and code exercises that accompany Part 1 of Aurelien Geron’s Hands-On Machine Learning textbook. It covers foundational ML concepts including classification, regression, SVMs, decision trees, ensemble methods, and dimensionality reduction using scikit-learn, along with deep learning fundamentals using Keras and TensorFlow. The content follows a hands-on approach with working code examples.