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Neural Networks And Learning Machines
Refocused, revised and renamed to reflect the duality of neural networks and learning machines, this edition recognizes that the subject matter is richer when these topics are studied together. Ideas drawn from neural networks and machine learning are hyb
864 pages, Paperback
First published September 13, 1993
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About the author
Simon Haykin
101Ìýbooks21ÌýfollowersSimon Haykin was a Canadian electrical engineer noted for his pioneering work in Adaptive Signal Processing with emphasis on applications to Radar Engineering and Telecom Technology. He was a Distinguished University Professor at McMaster University in Hamilton, Ontario, Canada.
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Displaying 1 - 2 of 2 reviews
November 8, 2020
A good ML book for those interested in Mathematical Proofs and completeness.
February 7, 2015
Recommendable. It concentrates on Neural network, including various approaches that I did not considered as Neural network - reinforcement learning, Kalman filter for instance. Explanations are relatively good.
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