Product Description

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.

Product Details

• Amazon Sales Rank: #94612 in Books
• Published on: 1997-10-01
• Original language: English
• Binding: Paperback
• 414 pages

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.

Customer Reviews

Excellent overview of all major machine learning topics.
I first used this book as the required text for my course in ML in 1997 and got rave reviews from the students. I will be using it again in 1999. I found ALL of the major topics and issues in ML addressed. The book is easily readable with anyone with a computer science background, and the book works quite well in a wide variety of approaches to presentation at the advanced undergraduate and graduate levels.

Complete Coverage of the topic
Covers Machine Learning concepts thoroughly, allowing you to decide which type is best for any particular problem. Uses some daunting mathematical notation, but still easy to follow

This book has proselytized me!!!!
Everything I will do in the future will be based on ML and just one semester of an ML course & this book has converted me(even though my major is not Comp.Science). Of-course this is due majorly to Dr. Thomas Ioerger and his teaching abilities(Texas A&M), but the book presents all concepts(even seemingly complex ones) in a way that is easy and enjoyable to learn. One of the most useful books I've ever studied!