- Aug 24, 2020
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- NL COIN
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.