Very Deep Neural Networks Explained in 40 Seconds
By Vincent Granville, Ph.D., Author at MLtechniques.com
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Very deep neural networks (VDNN) illustrated with data animation: a 40 second video, featuring supervised learning, layers, neurons, fuzzy classification, and convolution filters.
It is said that a picture is worth a thousand words. Here instead, I use a video to illustrate the concept of very deep neural networks (VDNN).
I use a supervised classification problem to explain how a VDNN works. Supervised classification is one of the main algorithms in supervised learning. The training set has four groups, each assigned a different color. The type of DNN described here is a convolutional neural network (CNN): it relies on filtering techniques.