Machine-Learning-Open-Cookbook

This repository contains Machine Leanring implementations for anyone to study. This is suppose to be used as teaching or self-study material, so the repository is structured in two branches:

• solutions, which includes Machine Learning implementations
• homeworks, which include only class and function definitions so that anyone can try to implement the algorithms by them self. This is the main brach of the repository.

Each method or model has its own folder, in which you can find, among others, the folowing files:

• lib.py, which contains the class definitions and implementations.
• data.csv, which is a toy dataset used to test the algorithm.
• notebook_[XX].ipynb, where we can test our implementations and hopefully help you gain some insights along the way. The XX is used to denote the order in which it should be read.

Additionally, the solutions branch may have a TUTORIAL.md file for each of the models explained, which is supposed to be a self contained blog post for the model in question.

Contents

1. Linear Regression
2. ...
3. ...

Contributors

This Machine Learning Open Cookbook is possible with the help of the following enthusiasts:

• srcolinas
• ...