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Published on Dec 26, 2012
Learning Deep Neural Networks using Restricted Boltzmann Machines in the Accord.NET 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.