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Neural Networks for Pattern Recognition (Advanced Texts in Econometrics)

Christopher M. Bishop




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 | #361618 in Books |  imusti |  1996-01-18 | Original language:English | PDF # 1 |  6.19 x1.12 x9.19l,1.71 | File type: PDF | 504 pages

 | Oxford University Press USA

||8 of 8 people found the following review helpful.| a little dated, but a good introduction|By sheep or goat|Great introduction to simple neural networks. It only covers feed-forward networks and not recurrent networks, so you don't get a full feel for the breadth of the neural networks field. Being from the early 1990's, it also doesn't cover any of the more recent advances in deep learning, which is a hot, and fascinating fi|.com |This book provides a solid statistical foundation for neural networks from a pattern recognition perspective. The focus is on the types of neural nets that are most widely used in practical applications, such as the multi-layer perceptron and radial bas

This is the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts, the book examines techniques for modeling probability density functions and the properties and merits of the multi-layer perceptron and radial basis function network models. Also covered are various forms of error functions, principal algorithms for error function minimalization, learning and generalizat...

You easily download any file type for your gadget.Neural Networks for Pattern Recognition (Advanced Texts in Econometrics)   |  Christopher M. Bishop. A good, fresh read, highly recommended.

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