Deep Belief Nets in C++ and CUDA C: Volume 3

Convolutional Nets

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Programming, Programming Languages, General Computing
Cover of the book Deep Belief Nets in C++ and CUDA C: Volume 3 by Timothy Masters, Apress
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Author: Timothy Masters ISBN: 9781484237212
Publisher: Apress Publication: July 4, 2018
Imprint: Apress Language: English
Author: Timothy Masters
ISBN: 9781484237212
Publisher: Apress
Publication: July 4, 2018
Imprint: Apress
Language: English

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.

What You Will Learn

  • Discover convolutional nets and how to use them

  • Build deep feedforward nets using locally connected layers, pooling layers, and softmax outputs

  • Master the various programming algorithms required

  • Carry out multi-threaded gradient computations and memory allocations for this threading

  • Work with CUDA code implementations of all core computations, including layer activations and gradient calculations

  • Make use of the CONVNET program and manual to explore convolutional nets and case studies

Who This Book Is For

Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

What You Will Learn

Who This Book Is For

Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.

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