This is a package for learning about neural networks through a simplified example. There are many other better packages for production use.
The chapters
folder contains a walk through for how to build up a neural network, starting with a simple linear classifier.
The source for a simple neural network that can have a variable number of layers each with a variable number of neurons can be found in src
.
There are examples using the code in src
for classifying XOR and MNIST image data. There is also an html file for visualizing how a linear classifier adjusts to classify AND.
Andrew Ng's Coursera class
Andrey Kurenkov's Brief History of Neural Networks and Deep Learning Parts I, II, III, and IV