Neural networks that run on geologic timescales.
Conceptually neural networks are very simple, but without much math background they can be hard to understand at first. This project aims to introduce neural networks starting with an object oriented model and only basic math in a code first, math second manner. Performance is very slow but can train an MNIST digit recognition network with decent accuracy and is easy to step through with a debugger.