Machine Learning

The field of machine learning is concerned with the question of how to construct computer programs that automatically improve with experience. In recent years many successful machine learning applications have been developed, ranging from data-mining programs that learn to detect fraudulent credit card transactions, to information-filtering systems that learn user’ reading preferences, to autonomous vehicles that learn to drive on public highways. At the same time, there have been important advances in the theory and algorithms that form the foundations of this field.

Contents
1. Concept Learning and the General-to-Specific Ordering.
2. Decision Tree Learning.
3. Artificial Neural Networks
4. Evaluating Hypotheses
5. Bayesian Learning
6. Computational Learning Theory.
7. Instance-Based Learning.
8. Genetic Algorithms
9. Learning Sets of Rules.
10. Analytical Learning
11. Combining Inductive and Analytical Learning.
12. Reinforcement Learning.