Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

This book is a comprehensive guide to building intelligent systems using deep learning techniques.

With practical examples and exercises, you'll learn how to implement machine learning models using Python frameworks like scikit-learn and TensorFlow.

You'll explore various training models, including support vector machines, decision trees, random forests, and ensemble methods, and dive into neural net architectures such as convolutional nets, recurrent nets, and deep reinforcement learning.

The author, a machine learning consultant and former Googler, provides clear explanations and code examples to help you master these techniques without getting bogged down in excessive theory or algorithm details.

Whether you're new to machine learning or looking to expand your skills, this book is the perfect resource for anyone interested in building intelligent systems using deep learning.