Dates

  • Hackathon: May 14 - May 23, 2021
  • Registration closes: May 7, 2021

Check out the schedule of relevant events here.

Description

Today, artificial intelligence and machine learning are being widely used for all sorts of useful and critical discoveries and pattern recognition. Tracking economies, predicting natural disasters, and training robots are just some of the incredible and fascinating things that are being done with machine learning this very minute. In an age of extreme technological development, it only makes sense that our students grow their understanding with it.

This virtual hackathon aims to encourage direct student involvement with contributed datasets from the UCI research community. The goal of every participating member/team is to use or develop machine learning approaches for the challenge datasets, in order to visualize, predict, clean/complete, analyze, or other such applications. Regardless of the domain - environmental, ethical, health, etc - we hope that the final submission that students draft will highlight something interesting about the data with which they become familiar. The most interesting submissions, as judged by experts in the challenge datasets, will receive monetary awards.

Successful teams may be encouraged to continue developing their project after the event jointly with UCI’s machine learning repository research team. Discoveries made from the Machine Learning Hackathon can be applied to other relevant datasets, or can spark a call for action on implementing a solution to an existing problem. All participants will create open source work, allowing other teams or researchers to further their initial progress.

Whether it be a simple, fascinating discovery or significant breakthrough, we are beyond excited to see what YOU can come up with!

Format

Submission and Evaluation Criteria: Click here.

This hackathon will last a little over a week. In that time, students will work individually, or in teams up to four people in size, to use machine learning to produce some interpretation of the dataset that they choose to work with. This does not have to be limited to programming a model aimed at achieving high accuracy. It can include, but is not limited to, creating visual representations of the data or improving its interpretability. Correspondence and announcements throughout the duration of the event will happen primarily through Slack. We will provide additional contact information there, if necessary. We will be arranging daily check-ins, meetings with dataset owners, and office hours, should anyone need guidance or assistance. There will be prizes offered to those groups that submit particularly useful or creative deliverables. We encourage students with any academic background or interest to participate!

Challenge Datasets

Organizers

Tamanna Hossain

Graduate Student, Computer Science

Faculty Mentors

  • Sameer Singh
  • Padhraic Smyth
  • Philip Papadopoulos

Contact Us

Organizer: tthossai@uci.edu

Slack (for registered participants only): uciml-hackathon.slack.com

Computing

Instructions: https://rcic.uci.edu/hackathon/

RCIC is generously providing computational resources for the hackathon. Go to the page above to see how to access the machines and run your jobs on the HPC. If you have any questions about the computing resources, post in the #computing channel on Slack.

Description

Today, artificial intelligence and machine learning are being widely used for all sorts of useful and critical discoveries and pattern recognition. Tracking economies, predicting natural disasters, and training robots are just some of the incredible and fascinating things that are being done with machine learning this very minute. In an age of extreme technological development, it only makes sense that our students grow their understanding with it.

This virtual hackathon aims to encourage direct student involvement with contributed datasets from the UCI research community. The goal of every participating member/team is to use or develop machine learning approaches for the challenge datasets, in order to visualize, predict, clean/complete, analyze, or other such applications. Regardless of the domain - environmental, ethical, health, etc - we hope that the final submission that students draft will highlight something interesting about the data with which they become familiar. The most interesting submissions, as judged by experts in the challenge datasets, will receive monetary awards.

Successful teams may be encouraged to continue developing their project after the event jointly with UCI’s machine learning repository research team. Discoveries made from the Machine Learning Hackathon can be applied to other relevant datasets, or can spark a call for action on implementing a solution to an existing problem. All participants will create open source work, allowing other teams or researchers to further their initial progress.

Whether it be a simple, fascinating discovery or significant breakthrough, we are beyond excited to see what YOU can come up with!

Frequently Asked Questions

  • I already have a team in mind. How do we register together?
    Every team member needs to register. We will be contacting you about teaming closer to the event.

  • Will there be prizes?
    Yes, most interesting submissions will receive monetary prizes.

  • Will computational resources be provided for the hackathon?
    Yes, we will be providing access to a cluster computing environment for registered hackathon participants. More details coming soon.

  • When will we be able to access the challenge datasets?
    Information about the challenge datasets have been released on this page. Datasets will become available to registered participants closer to the date of the event.