I created a demo in which you may see a multi-layer perceptron with dropout train on a dataset I created of hand drawn squares, circles, and triangles. This was made with the matplotlib animation function. The code will plot any dimensioned neural network when given the input sums and weight matrices between each layer and colors the nodes based on their saturation. It will take one training example from every 25 epochs and shows the forward pass of it computing as well as the cross-entropy loss and accuracy.