An RBM can extract features and reconstruct input data, but it still lacks the ability to combat the vanishing gradient. However, through a clever combination of several stacked RBMs and a classifier, you can form a neural net that can solve the problem. This net is known as a Deep Belief Network.
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The Deep Belief Network, or DBN, was also conceived by Geoff Hinton. These powerful nets are bel
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