This is a cross-platform, header-only library for machine learning and AI.
The standard stuff work fairly well AFAIK, but I do have some problems with the LeNet-5 implementation (see below).
The reason I wanted to implement LeNet-5 (by Yann LeCun) is to learn convolutional networks. My opinion is that you don't learn how these more advanced types of network work just by using PyTorch or TensorFlow etc, but you rather learn how to use those APIs. This is my attempt to actually understand how LeNet-5 works under the hood so that I can implement more advanced networks such as AlexNet. I've planned to add other types of machine learning techniques and networks such as LSTMs and Q-learning (RL) in the future.
The LeNet-5 code is a W.I.P. at the moment. The paper by Yann LeCun is a bit unclear on the details. The feed forward part is fairly straight forward, but issues start popping up when attempting to backprop the thing.