Machine Learning Workshop

With the inflow of large amounts of data taken by the next generation of telescopes, Machine Learning (ML) techniques are becoming more and more important for astronomers.

The goal of this 2-day workshop (held virtually at the AAS #237 on January 7+8, 2021) was to introduce several different ML techniques to scientists by hands-on tutorials. The workshop was specifically targeting beginners and intermediates in ML at all levels of their careers. The first day of the workshop focussed on entry-level tutorials introducing the techniques of supervised and unsupervised ML. The second day included more advanced tutorials and a longer Q&A to wrap up. During the workshop, no Python package installation was needed as all tutorials were taught in Jupyter notebooks that were run on Amazon Web Services instances.

All Jupyter Notebooks and other materials of the workshop can be downloaded here for free! The recordings of the tutorials are currently only available for members of the American Astronomical Society.

The workshop was organized by Caltech/IPAC together with the University of Illinois, Urbana-Champaign, and run on Amazon Web Services with Amazon credits.