As a proof of concept, this repository contains a single Python script with a full implementation of a framework for artificial neural networks while making use of no imports whatsoever. This means that the implementation is done purely in vanilla Python, without even resorting to the standard library.
Here are some of the things that had to be implemented
by hand because no import were allowed:
- pseudo-random number generation;
- matrices and matrix algebra:
- matrix addition and subtraction
- matrix multiplication and division with scalars
- matrix comparison with scalars
- matrix transpose
- classes for abstract activation and loss functions
- Leaky ReLU activation function
- MSE loss function
- layer and neural network classes
- forward pass and backpropagation
As of now, the code may have a bug that is preventing the neural network from learning on the MNIST dataset. To be sorted out soon, live on mathspp.com/twitch.