Rolling in the Deep: RBMs

Another type of networks used in deep learning are Restricted Boltzmann Machines (RBM). RBMs are shallow networks used for data reconstruction and feature extraction. Structurally, an RBM is a shallow neural net with just two layers -- the visible layer and the hidden layer. RBM is used for finding patterns and reconstructing the input in an unsupervised manner. The nodes are connected to each other across layers, but no two nodes in the same layer shares a connection, thus RBM is a symmetrical bipartite graph.