Minimal and clean examples of machine learning algorithms implementations
Switch branches/tags
Nothing to show
Clone or download
mxc19912008 and rushter Get the derivative of the loss function out of the for loop (#42)
I think getting the derivative of the loss function should be out of the for loop. There is no need to calculate the derivative function for max iteration times.
Latest commit e253211 Oct 23, 2018

README.md

Machine learning algorithms

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

Why?

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.

Implemented:

Installation

    git clone https://github.com/rushter/MLAlgorithms
    cd MLAlgorithms
    pip install scipy numpy
    pip install .

How to run examples without installation

    cd MLAlgorithms
    python -m examples.linear_models

How to run examples within Docker

    cd MLAlgorithms
    docker build -t mlalgorithms .
    docker run --rm -it mlalgorithms bash
    python -m examples.linear_models

Contributing

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.