1. Must know Python

2. Must have some knowledge and experience using scikit-learn, the Python machine learning library

3. Must have some familiarity with Git

PREPARATION (required)

1.  Read the scikit-learn Contributing documentation (30-minute read)

2.  Review scikit-learn open issues

3.  Must have a GitHub account

4.  Gitter

  • Gitter is an open source instant messaging and chat room system for developers and users of GitHub repositories. 
  • Join (use GitHub ID to sign in)

5.  Review Git (Git Resources)

6.  A Text Editor should be installed: 

  • Visual Studio Code (VSC)
  • Sublime Text
  • Atom
  • OR other preferred editor

7.  Python installed via Anaconda. (Anaconda includes Jupyter Notebook) 

PREPARATION (optional)

1.  Git workshop

2.  Andreas Mueller’s course, Applied Machine Learning is available online.  If you have time prior to the sprint, it is a helpful resource/refresher with references to scikit-learn library, specific features and code.


The plan is to work in pairs.  The goal is that each participant will be able to resolve one trivial fix and one actual fix.

We will setup using conda virtual environments.