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From: saswss@hotellng.unx.sas.com (Warren Sarle)
Subject: Recommendation: Bishop (1995) Neural Networks for Pattern Recognition
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Date: Fri, 26 Jan 1996 23:18:51 GMT
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Bishop, C.M. (1995). Neural Networks for Pattern Recognition,
Oxford: Oxford University Press. ISBN 0-19-853849-9 (hardback) or
0-19-853864-2 (paperback), xvii+482 pages.

This is definitely the best book on neural nets for practical
applications (rather than for neurobiological models). And it is the
_only_ textbook on neural nets that I have seen that is really
statistically solid.

"Bishop is a leading researcher who has a deep understanding of the
material and has gone to great lengths to organize it in a sequence that
makes sense. He has wisely avoided the temptation to try to cover
everything and has therefore omitted interesting topics like
reinforcement learning, Hopfield networks, and Boltzmann machines in
order to focus on the types of neural networks that are most widely used
in practical applications.  He assumes that the reader has the basic
mathematical literacy required for an undergraduate science degree, and
using these tools he explains everything from scratch. Before
introducing the multilayer perceptron, for example, he lays a solid
foundation of basic statistical concepts. So the crucial concept of
overfitting is introduced using easily visualized examples of
one-dimensional polynomials and only later applied to neural networks.
An impressive aspect of this book is that it takes the reader all the
way from the simplest linear models to the very latest Bayesian
multilayer neural networks without ever requiring any great intellectual
leaps." -Geoffrey Hinton, from the foreword. <P>

And, no, I'm not getting a kickback from the publisher. :-)
-- 

Warren S. Sarle       SAS Institute Inc.   The opinions expressed here
saswss@unx.sas.com    SAS Campus Drive     are mine and not necessarily
(919) 677-8000        Cary, NC 27513, USA  those of SAS Institute.
