Minimal and clean examples of machine learning algorithms implementations
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A collection of minimal and clean implementations of machine learning algorithms.
This project is targeting people who want 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.
git clone https://github.com/rushter/MLAlgorithms cd MLAlgorithms pip install scipy numpy python setup.py develop
cd MLAlgorithms python -m examples.linear\_models
cd MLAlgorithms docker build -t mlalgorithms . docker run --rm -it mlalgorithms bash python -m examples.linear\_models
Your contributions are always welcome!
Feel free to improve existing code, documentation or implement new algorithm.
Please open an issue to propose your changes if they are big enough.