Table of Contents

Getting Started with Machine Learning and Python

Building a Movie Recommendation Engine with Naïve Bayes

Recognizing Faces with Support Vector Machine

Predicting Online Ad Click-Through with Tree-Based Algorithms

Predicting Online Ad Click-Through with Logistic Regression

Scaling Up Prediction to Terabyte Click Logs

Predicting Stock Prices with Regression Algorithms

Predicting Stock Prices with Artificial Neural Networks

Mining the 20 Newsgroups Dataset with Text Analysis Techniques

Discovering Underlying Topics in the Newsgroups Dataset with Clustering and Topic Modeling

Machine Learning Best Practices

Categorizing Images of Clothing with Convolutional Neural Networks

Making Predictions with Sequences Using Recurrent Neural Networks

Making Decisions in Complex Environments with Reinforcement Learning

About the Author

Yuxi (Hayden) Liu is a machine learning software engineer at Google. Previously, he worked as a machine learning scientist in a variety of data-driven domains and applied his machine learning expertise in computational advertising, marketing, and cybersecurity. Hayden is the author of a series of machine learning books and an education enthusiast. His first book, the first edition of Python Machine Learning By Example, was ranked the #1 bestseller in its category on Amazon in 2017 and 2018 and was translated into many languages. His other books include R Deep Learning Projects, Hands-On Deep Learning Architectures with Python, and PyTorch 1.x Reinforcement Learning Cookbook.