Introduction to Machine Learning

Draft of Incomplete Notes

by

Nils J. Nilsson

[email protected]

http://ai.stanford.edu/~nilsson

Description (as of August 22, 2005):

This page has pointers to my draft book on Machine Learning and to its individual chapters.  They can be downloaded in Adobe Acrobat format. Although I have tried to eliminate errors, some undoubtedly remain---caveat lector. Certain elements of the typography (overflow into margins, etc.) have not been polished.

The notes survey many of the important topics in machine learning circa 1996. My intention was to pursue a middle ground between theory and practice. The notes concentrate on the important ideas in machine learning---it is neither a handbook of practice nor a compendium of theoretical proofs. My goal was to give the reader sufficient preparation to make the extensive literature on machine learning accessible. The draft is just over 200 pages (including front matter).

Download the Entire Book:

• Introduction to Machine Learning (2.5MB)

Download the Various Parts:

• Title Page
• Table of Contents and Preface
• Chapter One: Preliminaries
• Chapter Two: Boolean Functions
• Chapter Three: Using Version Spaces for Learning
• Chapter Four: Neural Networks
• Chapter Five: Statistical Learning
• Chapter Six: Decision Trees
• Chapter Seven: Inductive Logic Programming
• Chapter Eight: Computational Learning Theory
• Chapter Nine: Unsupervised Learning
• Chapter Ten: Temporal-Difference Learning
• Chapter Eleven: Delayed-Reinforcement Learning
• Chapter Twelve: Explanation-Based Learning
• Bibliography

Nils J. Nilsson
Artificial Intelligence Laboratory
Department of Computer Science
Stanford University
Stanford, CA 94305

[email protected]

http://ai.stanford.edu/~nilsson

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Copyright © 1996 Nils J. Nilsson. All rights reserved.