Selected Product: | Introduction to the Theory of Neural Computation (Santa Fe Institute Studies in the Sciences of Complexity) Paperback Author: John A. Hertz Publisher: Westview Press Release Date: 1991-01-01 ISBN-10: 0201515601 ISBN-13: 9780201515602 List Price: $59.00 Average Customer Rating: | | Pattern Recognition and Machine Learning (Information Science and Statistics) ISBN-10: 0387310738 ISBN-13: 9780387310732 List Price:$84.95 Principles of Neural Science ISBN-10: 0838577016 ISBN-13: 9780838577011 List Price:$120.00 Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems ISBN-10: 0262541858 ISBN-13: 9780262541855 List Price:$40.00 Biophysics of Computation: Information Processing in Single Neurons (Computational Neuroscience) ISBN-10: 0195181999 ISBN-13: 9780195181999 List Price:$65.00 Information Theory, Inference & Learning Algorithms ISBN-10: 0521642981 ISBN-13: 9780521642989 List Price:$62.00 |
To use our price comparison to get the cheapest price, please click on the "Find the Cheapest Price" button located above for Introduction to the Theory of Neural Computation (Santa Fe Institute Studies in the Sciences of Complexity) by John A. Hertz (ISBN-10: 0201515601, ISBN-13: 9780201515602). At this time we have not yet written a review for Introduction to the Theory of Neural Computation (Santa Fe Institute Studies in the Sciences of Complexity) by John A. Hertz (ISBN-10: 0201515601, ISBN-13: 9780201515602). Please continue to keep checking back to this page as we are constantly adding reviews. Summaries and Customer Reviews are supplied by Amazon.com This book is a comprehensive introduction to the neural network models currently under intensive study for computational applications. It is a detailed, logically-developed treatment that covers the theory and uses of collective computational networks, including associative memory, feed forward networks, and unsupervised learning. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest. Clear and logical exposition | Customer Rating: | It's not the latest book on this topic, so today, there are other texts that have more recent developments to be sure. I originally read this text about 15 years ago. But what I got from this book, that I didn't get from most, are important insights and clear understanding of the material that's covered. The authors have a deep understanding, and have teaching as their goal in writing. Most other texts in this area are lacking in one or both of those characteristics, and aren't worth the paper they are printed on. | Introduction to the Theory of Neural Computation | Customer Rating: | | This book is written from a mathematical perspective. The book introduces the Hopfield Neural Network with history and applications. The authors solve the network problem and develop the Hebb Rule. Links are made to Ising Spin models and stochastic problems. I find this book to be one of the best written mathematical guides for Neural Networks. | A Broad Survey | Customer Rating: | | This was a good survey, and well-grounded mathematically. It is kind of scattershot, and if you primarily want to do practical projects like predicting financial markets, a lot of the sections won't be relevant. But if you want a broad-based approach, emphasizing a variety of network designs fro different purposes, this book is very good. |
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