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4 Reviews
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9 of 10 people found the following review helpful:
5.0 out of 5 stars
For beginners and graduate students,
By Sungjin Park (Melbourne, FL USA) - See all my reviews
This review is from: Principles of Neurocomputing for Science and Engineering (Hardcover)
I strongly recommend this text for beginners and graduate students who want to understand Neural Networks. First, the text book explains the why, where, and how to apply Neural Networks, which is the most important point for understanding Neural Networks. Second, mathematical proofs, clear description of algorithms and MATLAB codes encourage me to do it myself. And a lot of mathematical foundation in the Appendix allow me to understand quite easily complex mathematical concepts.
5.0 out of 5 stars
Best neural network textbook for beginners,
By
This review is from: Principles of Neurocomputing for Science and Engineering (Hardcover)
This is definitely a must read for all NN beginners. In my opinion, this book is very well organized. First, it puts theoretical stuff and applicaiton examples into separate parts (Part I&II). Second, in Part I, it starts with basic constituents of NNs: one neuron NN, activation fucntion, learning rule,...and then covers NNs of more large-scale types. Within each type, it describes the most rudementary or prototype NN first, supplements info regarding other variants next, and mentions the issues to be encountered for actual implemention. This all makes this book so easy to follow. I can quickily decide whether I can skip the coming section/subsection and no worry of discontinuity as I read along.
0 of 1 people found the following review helpful:
5.0 out of 5 stars
For beginners and graduate students,
By Sungjin Park (Melbourne, FL USA) - See all my reviews
This review is from: Principles of Neurocomputing for Science and Engineering (Hardcover)
I strongly recommend this text for beginners and graduate students who want to understand Neural Networks. First, the text book explains the why, where, and how to apply Neural Networks, which is the most important point for understanding Neural Networks. Second, mathematical proofs, clear description of algorithms and MATLAB codes encourage me to do it myself. And a lot of mathematical foundation in the Appendix allow me to understand quite easily complex mathematical concepts.
0 of 2 people found the following review helpful:
1.0 out of 5 stars
Horrible book ! One of the most hardest to read books out there,
This review is from: Principles of Neurocomputing for Science and Engineering (Hardcover)
This book has no flow. It expects you to know lots of its own new jargon making it extremely hard to read. Not recommended for a course in neurocomputing.
Reading the chapers does not help you to solve the problems at the end of chapter. The problems are a chapter on their own. Stay away from this book !!! |
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Principles of Neurocomputing for Science and Engineering by Fredric M. Ham (Hardcover - September 29, 2000)
Used & New from: $32.63
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