Deep belief nets are one of the most exciting recent developments in artificial intelligence. 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. 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. This book presents the essential building blocks of a common and powerful form of deep belief net: convolutional nets. These models are especially useful for image.
Deep Belief Nets in C++ and CUDA C: Volume III: Convolutional Nets (Volume 3) books pdf online
Deep Belief Nets in C++ and CUDA C: Volume III: Convolutional Nets (Volume 3) read online
Timothy Masters ebooks downloads
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