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


I have written a project https://github.com/memoiry/lightML.jl including basic implementation of typical machine learning algorithms implemented in Julia. It’s a self-educational project so that the implementation is quite basic, clear and easier to follow than the optimized libraries.

Also, I have wrapped the project into a Julia module, which makes it extremely easy to play with. For example, you can clone, load the module and then call test_svm() for testing SVM. Every machine learning algorithm implemented now have a test function for testing purpose.

Hope someone could find it helpful and any contribution is welcome!