| Document Type
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BL
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| Record Number
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851099
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| Main Entry
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Masters, Timothy
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| Title & Author
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Deep belief nets in C++ and CUDA C.\ Timothy Masters.
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| Publication Statement
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New York :: Apress,, [2018]
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, ©2018
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| Series Statement
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ITpro collection
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| Page. NO
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1 online resource :: illustrations
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| ISBN
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148423720X
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: 1484237218
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: 9781484237205
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: 9781484237212
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9781484237205
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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1. Feedforward Networks -- 2. Programming Algorithms -- 3. CUDA Code -- 4. CONVNET Manual.
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| Abstract
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Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a 'thought process' that is capable of learning abstract concepts built from simpler primitives. These models are especially useful for image processing applications. At each step Deep Belief Nets in C++ and CUDA C: Volume 3 presents intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. Source code for all routines presented in the book, and the executable CONVNET program which implements these algorithms, are available for free download.
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| Subject
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C++ (Computer program language)
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Neural networks (Computer science)
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Artificial intelligence.
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Business mathematics systems.
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C++ (Computer program language)
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COMPUTERS-- Programming Languages-- C++.
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Databases.
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Neural networks (Computer science)
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Programming scripting languages: general.
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| Dewey Classification
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006.32
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| LC Classification
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QA76.87
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| Parallel Title
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Convolutional nets
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