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Book review: Neural Network Learning and Expert Systems by Stephen L. Gallant (MIT Press, Cambridge, MA, 1993)

Book review: Neural Network Learning and Expert Systems by Stephen L. Gallant (MIT Press,... There is an abundance of literature on Neural Networks (NNs). However, it is hard to find a text on NNs that provides a happy balance among good pedagogy, theory, and practice. For example, most introductory NN courses are taught with a collection of loosely related papers, excerpts from books, or software packages. A novice attempting to learn the subject without a good instructor inevitably becomes lost in an array of inconsistent terminology, complicated mathematics, and diverse methodologies and usually does not obtain a firm grasp of the basic foundations of the subject. Steve Gallant's book "Neural Network Learning and Expert Systems" is a good effort towards alleviating these problems. In addition, the book introduces a method to integrate the best features of NNs and expert systems (ESs). The goals of the book are (1) to provide a systematic development of NN learning algorithms suitable for researchers and students and (2) to present NN expert systems. The former goal is largely met and thus renders the book well-suited for self-directed study or for primary reading in a graduate or upper-level undergraduate NN course. The latter goal is met also, although the book lacks sufficient comparison with alternative approaches to the integration of NNs and ESs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGART Bulletin Association for Computing Machinery

Book review: Neural Network Learning and Expert Systems by Stephen L. Gallant (MIT Press, Cambridge, MA, 1993)

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Publisher
Association for Computing Machinery
Copyright
Copyright © 1994 by ACM Inc.
ISSN
0163-5719
DOI
10.1145/181668.1064812
Publisher site
See Article on Publisher Site

Abstract

There is an abundance of literature on Neural Networks (NNs). However, it is hard to find a text on NNs that provides a happy balance among good pedagogy, theory, and practice. For example, most introductory NN courses are taught with a collection of loosely related papers, excerpts from books, or software packages. A novice attempting to learn the subject without a good instructor inevitably becomes lost in an array of inconsistent terminology, complicated mathematics, and diverse methodologies and usually does not obtain a firm grasp of the basic foundations of the subject. Steve Gallant's book "Neural Network Learning and Expert Systems" is a good effort towards alleviating these problems. In addition, the book introduces a method to integrate the best features of NNs and expert systems (ESs). The goals of the book are (1) to provide a systematic development of NN learning algorithms suitable for researchers and students and (2) to present NN expert systems. The former goal is largely met and thus renders the book well-suited for self-directed study or for primary reading in a graduate or upper-level undergraduate NN course. The latter goal is met also, although the book lacks sufficient comparison with alternative approaches to the integration of NNs and ESs.

Journal

ACM SIGART BulletinAssociation for Computing Machinery

Published: Jan 1, 1994

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