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OpenML-AutoML Tutorial JADS

Schedule

Open Machine Learning

Time Topic
09:00 - 09:30 Introduction to OpenML
09:30 - 10:30 OpenML Python tutorial
10:45 - 12:15 OpenML Hands-on

Automated Machine learning

Time Topic
13:15 - 14:45 Introduction to AutoML
15:00 - 16:30 AutoML Hands-on

Choose your Jupyter environment

There are several options:

  • JADS Jupyter environment

    • Download (or clone) this github repository. Locate the notebook folder.
    • In your JADS Jupyter environment, create a new folder, click the upload button, and upload everything from the notebook folder into that new folder
    • Open and run the Python setup notebook to install all dependencies
    • Verify that everything installs correctly
  • Binder

    • Click the Binder button on the website to start a new environment on myBinder. This will start a docker image, so it may take a few minutes.
  • Google Colab

    • We provided links to Google Colab notebooks on the website. You need to make your own copy of each of them via File > Save Copy in Drive
  • Set up your own environment

    • OpenML part: Instructions are available in the beginning of the OpenML Python tutorial
    • AutoML part: Do the setup as in the Python setup notebook. Note: Autosklearn does NOT run on Windows

Preparation

  • Create an OpenML account on http://www.openml.org - this is needed for uploading things to the platform
  • If you have interesting data to work with, please bring it along.
    • Open datasets can be shared during the hands-on session.
    • Any canonical machine learning problems (classification/regression) can be experimented with during the AutoML hands-on session.