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Title: Understanding Neural Networks by John Iovine ISBN: 0-7906-1115-5 Publisher: Delmar Learning Pub. Date: 01 September, 1998 Format: Paperback Volumes: 1 List Price(USD): $32.95

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Average Customer Rating: 3 (3 reviews)

Rating: 3
Summary: Good Introduction
Comment: The book is actually a fairly good introduction to what neural networks are and how to use them.

If you don't know anything about neural networks, it is an good way to learn about how to use them. Having said that, there are some bad points. I found a few errors in the description of how backpropagation works (page 141 says "WA = -1.1 x .35 x .15, so WA = 0.21", when WA should be -0.05775).

As well the NetTalk project isn't finished yet, and I didn't see anything on the website that is supposed to have it. I suspect it never worked properly...

The book does use the BASIC language, but the language isn't really that important.

Don't expect this book to teach you how to make a good neural network in a programming language. You will need another book to cover them in more detail. However if you want an introduction to neural networks this book may well be a good choice

Rating: 1
Summary: Useless!!!
Comment: I totally disagree with the previous reviewer. This book is the worst I have ever read. It's stucked in a dusty past. I am wondering if the author has ever done anything about computing except a few solderings here and there.

The GA-lover than I am was shocked after one sentence: "Computer scientists generally agree there are two paths to generating artificial intelligence (AI) in computers; rule-based systems and neural networks."

Hearing about GOTO and GOSUB in the second paragraph, I almost dropped reading. Later I still encountered a two-pages explanation about where to find and why/how to use QBasic.

Sometimes, the author introduces an interesting topic. Never seen the flesh coming, though. And it's so badly written...

There is nothing in this book that a good INTERNET TUTORIAL would not cover in a hundred words, so please, do yourself a favor and jump to your favourite search engine. Would save your time, either as a beginner or as an ANN guru! I used to go through a few of them myself and learned so much more than reading this book!

I had previously seen very negative comments about this book but forgot where. I decided to ignore them. Bad idea!!! Really bad bad bad bad bad idea!!!

Sure, I will now avoid all books from this author...

Rating: 5
Summary: This is by far the best book I've found on neural networks.
Comment: This is by far the best book I've found on learning about neural networks. Most other neural network books I've read are more confusing than illuminating. In this book you learn everything you need to know, all the basics, from a neuron up to multi-layer Back-Propagation network that solves the XOR problem. You learn about neurons, biological, mathematical and electronic. I learned what weights are, how the weight influences a signal and relates to the neuron, summations, thresholds, weight adjustments and how to bias a neuron (or layer). The book illustrates how to program these concepts into working neural networks using the Basic Language. The book shows how various networks paradigms work, like Perceptron, Hopfield Nets, BAM, Adaline, Self-Organizing and of course Back-Propagation Networks. If that isn't enough, it also teaches how to build simple electronic networks that perform useful functions. A super book, my highest recommendation.