Deep Belief Nets - Ep. 7 (Deep Learning SIMPLIFIED)

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. The Deep Belief Network, or DBN, was also conceived by Geoff Hinton. These powerful nets are believed to be used by Google for their work on the image recognition problem.