Deep Belief Nets in C++ and CUDA C. Volume 1, Restricted Boltzmann machines and supervised feedforward networks / Timothy Masters.
Masters, Timothy, author.
2018
QA76.87 .M368 2018
Available Online

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Title Deep Belief Nets in C++ and CUDA C. Volume 1, Restricted Boltzmann machines and supervised feedforward networks / Timothy Masters.
Author Masters, Timothy, author.
ISBN 9781484235911 (electronic book)
1484235916 (electronic book)
9781484235904
DOI https://doi.org/10.1007/978-1-4842-3591-1
Published New York, NY : Apress, [2018]
Language English
Description 1 online resource : illustrations
Item Number 10.1007/978-1-4842-3591-1 doi
Call Number QA76.87 .M368 2018
Dewey Decimal Classification 006.32
Summary Discover the essential building blocks of the most common forms of deep belief networks. At each step this book provides 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. The first of three in a series on C++ and CUDA C deep learning and belief nets, Deep Belief Nets in C++ and CUDA C: Volume 1 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. As such, you’ll see that a typical deep belief net can learn to recognize complex patterns by optimizing millions of parameters, yet this model can still be resistant to overfitting. All the routines and algorithms presented in the book are available in the code download, which also contains some libraries of related routines. You will: Employ deep learning using C++ and CUDA C Work with supervised feedforward networks Implement restricted Boltzmann machines Use generative samplings Discover why these are important.
Note Includes index.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Source of Description Online resource; title from PDF title page (viewed May 02, 2018).
Available in Other Form Print version: 9781484235904
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Record Appears in Online Resources > Ebooks
All Resources
1. Introduction
2. Supervised Feedforward Networks
3. Restricted Boltzmann Machines
4. Greedy Training: Generative Samplings
5. DEEP Operating Manual.

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