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Machine Learning : A Theoretical Approach - Balas K. Natarajan

Machine Learning

A Theoretical Approach

Hardcover

Published: 1st September 1991
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This is the first comprehensive introduction to computational learning theory. The author's uniform presentation of fundamental results and their applications offers AI researchers a theoretical perspective on the problems they study. The book presents tools for the analysis of probabilistic models of learning, tools that crisply classify what is and is not efficiently learnable. After a general introduction to Valiant's PAC paradigm and the important notion of the Vapnik-Chervonenkis dimension, the author explores specific topics such as finite automata and neural networks. The presentation is intended for a broad audience--the author's ability to motivate and pace discussions for beginners has been praised by reviewers. Each chapter contains numerous examples and exercises, as well as a useful summary of important results. An excellent introduction to the area, suitable either for a first course, or as a component in general machine learning and advanced AI courses. Also an important reference for AI researchers.

Introduction
Learning Concept on Countable Domains
Time Complexity of Concept Learning
Learning Concepts on Uncoutable Domains
Learning Functions
Finite Automata
Neural Networks
Generalizing the Learning Model
Conclusion
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9781558601482
ISBN-10: 1558601481
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 217
Published: 1st September 1991
Country of Publication: US
Dimensions (cm): 23.67 x 16.0  x 2.39
Weight (kg): 0.52