This project is an attempt to create a simple machine learning library containing implemenations of a commonly used algorithms implemented in a way that is easy to understand.
The requirements can be installed by running:
pip install -r requirements.txt
- Peter Roelants' guide to Implementing neural networks
- Chris McCormick's guide to understanding PCA
- CS231n's section about kNN
Begin by downloading the MNIST dataset from the MNIST database
homepage. The location of the dataset is
hardcoded to data in the file nn_mnist.py, but feel free to change it.
After having installed the requirements, you should be able to run
python -m examples.nn_mnist, which trains the network
and prints the final accuracy.