Introduction

This tutorial will cover some demonstrations of basic machine learning analysis implementations in Python. If there is a general demand for other demonstrations or tutorials, they will be added here throughout the course. To get started, you will need a basic understanding of Python as well as access to a Python development environment with the following packages installed:

• numpy (used for numeric computation)
• scikit-learn (machine learning methods)
• matplotlib (for plotting)

ugradx, gradx, hhpc and marcc all provide such an environment. For the purposes of this course, all submitted code should run without errors on ugradx or gradx. If you would also like to work locally, you may install the above packages using pip, e.g.:

pip install numpy
pip install scikit-learn
pip install matplotlib

Depending on your system configuration, you may need to run the above commands using sudo. You may also install these packages through Conda if you prefer.

Let's begin!

Special thanks to Princy Parsana for her work on the first iteration of this tutorial.