Deep Belief Nets in C++ and Cuda C

Deep Belief Nets in C++ and Cuda C by Timothy Masters

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.

SKU	Non disponible
ISBN 13	9781507751473
ISBN 10	1507751478
Titre	Deep Belief Nets in C++ and Cuda C
Auteur	Timothy Masters
État	Non disponible
Type de reliure	Paperback
Éditeur	Createspace Independent Publishing Platform
Année de publication	2015-02-11
Nombre de pages	244
Note de couverture	La photo du livre est présentée à titre d'illustration uniquement. La reliure, la couverture ou l'édition réelle peuvent varier.
Note	Non disponible