Python Machine Learning 3rd Edition

Applied machine learning with a solid foundation in theory. Revised and expanded with TensorFlow 2, GANs, and reinforcement learning.

Key Features

  • Third edition of the bestselling, widely acclaimed Python machine learning book
  • Clear and intuitive explanations take you deep into the theory and practice of machine learning in Python
  • Fully updated and expanded to cover Generative Adversarial Network (GAN) models, reinforcement learning, TensorFlow 2, and modern best practice

Book Description

Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a clear step-by-step tutorial, and a reference you’ll keep coming back to as you build your machine learning systems.

Packed with clear explanations, visualizations, and worked examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself.

This new third edition is updated for TensorFlow 2.0 and the latest additions to scikit-learn. It’s expanded to cover cutting-edge reinforcement learning techniques based on deep learning as well as an introduction to Generative Adversarial Networks.

This book is your companion, whether you’re a Python developer new to machine learning or want to deepen your knowledge of the latest developments.

What you will learn

  • Understand the key frameworks in data science, machine learning, and deep learning
  • Harness the power of the latest Python open source libraries in machine learning
  • Explore machine learning techniques using challenging real-world data
  • Master deep neural network implementation using the TensorFlow library
  • Learn the mechanics of classification algorithms to implement the best tool for the job
  • Predict continuous target outcomes using regression analysis
  • Uncover hidden patterns and structures in data with clustering
  • Delve deeper into textual and social media data using sentiment analysis

Who This Book Is For

If you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential and unmissable resource. Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for developers and data scientists who want to teach computers how to learn from data.


About The Author

Sebastian Raschka

Vahid Mirjalili