Deep neural networks visualization
In this publication I present a "toy tool" to see how neurons on a Deep Neural Network (DNN) modify the links between them. These links are also called Weights. For those with technical knowledge, the "bias" unit is not shown (Because of lack of time, I will upgrade it later). In addition I haven't implemented yet the predict option, I would probably add it later. Technical Notes: This DNN uses standard back propagation without optimizations such as Adam optimizer or regularization parameters. I am using Math.js for the matrix operations. There are some errors I haven't figured out yet how to solve them, specially for Nan values that will appear when showing the visualization (Sometimes happens, no worry =) ) The last layer, the output layer is a sigmoid layer by default. Maybe later I will implement a linear function for regression analysis. And it has been implemented for binary classification by the moment. The weights are randomly init...