Machine learning algorithms

A collection of minimal and clean implementations of machine learning algorithms.

Why?

This project is targeting people who wants to learn internals of ml algorithms or implement them from scratch.
The code is much easier to follow than the optimized libraries and easier to play with.
All algorithms are implemented in Python, using numpy, scipy and autograd.

Implemented:

TODO:

• t-SNE
• MCMC
• Word2vec
• Naive bayes
• K-nearest neighbors
• Adaboost
• HMM

Installation

    git clone http://ift.tt/2eubcVS
    cd MLAlgorithms
    pip install scipy numpy
    pip install .

How to run examples without installation

    cd MLAlgorithms
    python -m examples/linear_models

Contributing

Your contributions are always welcome!