Using a restricted Boltzmann machine to reconstruct Bangla MNIST images

A restricted Boltzmann machine (RBM) is an unsupervised model. As an undirected graphical model with two layers (observed and hidden), it is useful to learn a different representation of input data along with the hidden layer. This was the first structural building block of deep learning, particularly when the computational resources to learn about a deep neural net with backpropagation were not available (a stacked RBM was used instead). It restricts the connectivity of the network (only allowing a bipartite graph in between the hidden and observed set of nodes) to make inference easy. It is an energy-based model; the joint distribution is modeled using the energy function. To infer the most probable observation, we need to choose the one with the...