Sample: Deep Neural Networks

Learning Deep Neural Networks using Restricted Boltzmann Machines in the Framework. Please turn the annotations on for a complete description of the video. In the video, intermediate layers are trained using the unsupervised Convergence-Divergence learning algorithm. The final layer is learned through Resilient Backpropagation. After the network has been trained, a final standard backpropagation is performed to fine-tune all weights in the network. The networks are created to extract features classify handwritten digits of the Optdigits dataset from the UCI’s Machine Learning Reposity. project page Project forums and discussion groups are at