Chapter 1. Introduction
Chapter 2. Concept Learning and the General-to-Specific Ordering
Chapter 3. Decision Tree Learning
Chapter 4. Artificial Neural Networks
Chapter 5. Evaluating Hypotheses
Chapter 6. Bayesian Learning
Chapter 7. Computational Learning Theory
Chapter 8. Instance-Based Learning
Chapter 9. Inductive Logic Programming
Chapter 10. Analytical Learning
Chapter 11. Combining Inductive and Analytical Learning
Chapter 12. Reinforcement Learning.

Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data.
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