This a machine learning library that achieves Model accuracy of about 95% on the MNIST dataset, its built on top of numpy
Heavily inspired by https://github.com/karpathy/micrograd and https://github.com/geohot/tinygrad
This is an educational project. I wish to learn how machine learning libraries work under the hood
You can train the model by executing the following command:
python mnist.py
- Add support for GPUs (Triton??)
- Build some model on top of this
- [.] DQN on cartpole
- VAE on on MNIST
- Move away from numpy
- Add tests