Table of contents : Cover Front Matter 1. The Basics of Machine Learning 2. The Statistics of Machine Learning 3. Model Selection and Regularization 4. Discriminant Analysis, Nearest Neighbor, and Support Vector Machine 5. Tree Modeling 6. Artificial Neural Networks 7. Deep Learning 8. Sentiment Analysis Back Matter