This repository contains supporting material to the Data Mining course being taught in the Summer of 2018 at the Seattle campus. For the most part, the material you will find here is made up of Jupyter Notebooks that will be covered in class, and that illustrate Python implementations of some of the concepts we will discuss. Another set of notebook files will serve as reference for specific homework assignments, and those will be explicitly highlighted as such.
All communication/announcements related to the course will be done via Slack. As a registered student, you should have access to our slack group here.
Everaldo Aguiar and Reid Johnson will be your course instructors, and if you come across any questions as you go over the notebook files available here, feel absolutely free to reach out to them directly (on Slack).
A large portion of the code snippets that are provided here were adapted from material that is freely available online. As such, you are strongly encouraged to review these (and any other relevant sources you may find) if you wish to improve your Python skills.
- Official scikit-learn Examples
- Official pandas Tutorials
- Donne Martin's Data Science Python Notebooks
- Official Materials and Notebooks for "Python for Data Analysis" by Wes McKinney
- Official Materials and Notebooks for "Python Data Science Handbook" by Jake VanderPlas
- Materials and Notebooks for "Programming Collective Intelligence" By Toby Segaran