RBM-and-DBN-on-MNIST

RBM and DBN over MNIST dataset When talking about deep learning the simplicity, scalability, flexibility and adaptive computation time of a model are some of the significant aspect of measuring the performance metric. With progress in the field of AI, it became possible to process complex task like recognizing features like real-life objects and human speech. However, with advancement in AI, came new challenges such as the vanishing gradient problem and redundant features. This led to the rise in RBM & DBN.