Join us for an in-person hackathon event at the University of Colorado Boulder! This event will provide an introduction to the NSF Harnessing the Data Revolution (HDR) Machine Learning Challenge, including a venue to form a team and get started with a submission. 

This two-day event will include a "main" day (Friday, Dec. 12) and an optional "working" day (Monday, Dec. 15). The main day will include presentations on each of the three benchmarks used for this year's challenge, an overview of the Codabench platform, an overview of CyVerse compute resources that will be available to participants, and a code-along session to demonstrate how to create a submission for the challenge. All the remaining time will be dedicated to team formation and trying out the challenge, all with organizers available to answer questions.

Note on experience: This event is intended to bring together participants with varied areas of expertise (e.g., computer science, environmental science, biology, etc.) for an interdisciplinary problem solving challenge.  Some coding experience (e.g., Python, R, etc.) is recommended, but this event is open to participants from any career stage (e.g., students, postdocs, researchers, faculty, private sector scientists and developers, etc.) and background.

About the Harnessing the Data Revolution ML Challenge

Challenge goal: Predict out of domain events, actions, and climactic conditions using open scientific data. 

Challenge timeline: Challenge runs through Jan. 31. 

Challenge prizes: 

• Total cash prizes $4000
• Cloud credits from AWS and NVIDIA for the winners.
• NVIDIA is also providing $400 in cloud credits to teams for training on their model.
• Prize from AMD, to be determined
• Special jury prizes include funded invitations to present their solution at award ceremony
  *There may be additional prizes yet to be determined.

This event is being organized by: 

• The National Ecological Observatory Network (NEON), Battelle
• The Environmental Data Science Innovation & Impact Lab (ESIIL), CU Boulder
• The Imageomics Institute
• CyVerse, University of Arizona
• iHARP