ML4SCI Hackathon

ML4SCI Hackathon 2021

We are pleased to announce the Machine Learning for Science (ML4SCI) 2021 Hackathon Competition that will take place from November 8-22, 2021. The ML4SCI competition is hosted by several campuses in the US including Puerto Rico and across the world, and is open to everyone. Participants will have the option of competing online or in-person. The hackathon will focus on applying machine learning techniques to scientific challenges, including those from the fields of physics, astronomy and planetary science.

Please find the competition poster at this link: https://bit.ly/3vOEtyN

The agenda for the hackathon can be found here: https://indico.cern.ch/event/1085878/

Anyone interested in learning more about machine learning techniques and trying their hand at the competition is welcome. Participants are encouraged to self-organize into small teams or work on their own to devise unique solutions to the challenge(s). The participants can work on the challenges on their own schedule. The competition will run for two weeks, however only a small fraction of that time is needed to obtain competitive results. Participants will have opportunities to interact with the organizers and with each other in person, via Zoom and on Slack. The kickoff meeting will be on Monday, November 8 (5 PM EDT) in person and on Zoom https://bit.ly/2YzCty3. There will also be an introductory machine learning lecture by Prof. Harrison Prosper on Tuesday, November 9 (2:30 PM EDT).Please see the Hackathon Slack page for in-person meeting details. Winners will receive certificates and prizes.

Interested participants can register via Slack at https://bit.ly/3arK2t2

There are six main challenges:

Please find more details and example Jupyter notebooks inside each challenge folder.

Solutions are due on Monday, November 22 at 7pm EDT/6pm Central time. Winners will receive certificates and prizes. For any questions about the ML4SCI Hackathon please contact Prof. Sergei Gleyzer sgleyzer@ua.edu


Contacts

ML4SCI Admins ml4-sci@cern.ch