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Last Commit
Sep. 22, 2017
Feb. 5, 2017

Machine Learning From Scratch

Python implementations of some of the foundational Machine Learning models and algorithms from scratch.

While some of the matrix operations that are implemented by hand (such as calculation of covariance matrix) are available in numpy I have decided to add these as well to make sure that I understand how the linear algebra is applied. The reason the project uses scikit-learn is to evaluate the implementations on sklearn.datasets.

The purpose of this project is purely self-educational.

Feel free to reach out if you have ideas about how to expand this project.

Current implementations:

Supervised Learning:

Unsupervised Learning: