MACHINE LEARNING TEXTBOOK: FREE INSPECTION COPIES
McGraw Hill announces immediate availability of a new textbook,
MACHINE LEARNING, by Tom Mitchell. This book provides a thorough,
multi-disciplinary introduction to computer algorithms for automated
learning and datamining.
Free copies are available to course instructors who will consider the
book for possible course adoption next fall or spring. To request a
copy, contact Betsy Jones at McGraw Hill (630)789-5057.
The chapter outline is:
1. Introduction
2. Concept Learning and the 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
(414 pages)
This book is intended for upper-level undergraduates, graduate
students, and professionals working in the area of datamining, machine
learning, and statistics. The text includes over a hundred homework
exercises, along with web-accessible code and datasets (e.g., neural
networks applied to face recognition, Bayesian learning applied to
text classification).
For further information, see http://www.cs.cmu.edu/~tom/mlbook.html.
To order by credit card call McGraw Hill 1-800-338-3987, ask for ISBN
number 0070428077.