Machine Learning (McGraw-Hill Series in Computer Science) - Hardcover

Mitchell, Thomas

Hardcover

ISBN 10: 0070428077 ISBN 13: 9780070428072

Publisher: McGraw-Hill Education, 1997

Synopsis

This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.

About this title

From the Publisher

No other book covers the concepts and techniques from the various fields in a unified fashion.
Covers very recent subjects such as genetic algorithms, reinforcement learning, and inductive logic programming.
Writing style is clear, explanatory and precise.

From the Author

Table of Contents:

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

Includes web-accessible data and code.

Edition details

• Publisher: McGraw-Hill Education
• Publication date: 1997
• Language: English
• ISBN 10: 0070428077
• ISBN 13: 9780070428072
• Binding: Hardcover
• Number of pages: 432