Deep Belief Nets in C++ and CUDA C: Volume 1: Restricted Boltzmann Machines and Supervised Feedforward Networks free ebook download.

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Deep Belief Nets in C++ and CUDA C: Volume 1: Restricted Boltzmann Machines and Supervised Feedforward Networks free ebook download

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C and CPP

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Catalogue

Author(s):	Timothy Masters

Date:	2018-06-20	Format:	PDF,EPUB	Language:	English	ISBN/ASIN:	1484235908
Pages:	219	OCR:		Quality:		ISBN13:	9781484235904
Uploader:	stirkout	Upload Date:	4/24/2018 8:32:49 PM

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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.

What You Will Learn

* 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

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.
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, youll 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.

Links Table

	Title	Link	Password	Size (MB)	Thank to	Inform Admin
2160187	Book	http://tezfiles.com/file/59f50c084e2e6...		5.63	stirkout

Tags: Belief Boltzmann CUDA Deep Feedforward Machines Nets Networks Restricted Supervised

Title	Link	Password	Size	Reason

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