This repository is the accompnying code which goes with my machine learning introductory class. The lecture notes for this course can be found on my webpage (https://jorisguerin.github.io/) under Teaching or directly downloaded here.
The lecture notes are intended to give the reader all the necessary material to get started quickly with Machine Learning. It provides some pointers to understand the kind of problems that are solved using machine learning as well as the underlying ideas behind a few algorithms. Purposely, these notes do not go into the mathematics of ML. However, it provides implementation exercises using Python and Scikit-learn, so that the reader can start making practical use of Machine Learning quickly.
The supplementary material for these notes can be found on this page. It contains solutions to each problem presented in the lecture notes in the form of python files (under Exercises). It also contains some example code to get started with python, numpy and scikit-learn (under Helpers). Note that each correction file has a list of useful functions at the beginning of the file. They can be used to complete the different assignments.