The Machine Learning Marathon (MLM26) is UW–Madison’s 4th annual semester-long ML/AI hackathon. From September through December, teams tackle real-world challenges hosted on Kaggle, spanning a range of skill levels, application areas, and ML/AI methods. Most challenges are inspired or directly sourced from labs at UW–Madison — see past challenges for examples.
Teams are supported throughout with hands-on cloud workshops (AWS, Google Cloud), compute credits, ML/AI and domain-expert advisors, and ML+X Nexus, our community-maintained resource hub for ML/AI work at UW–Madison.
We’re currently in the challenge & advisor recruitment phase — join the ML+X Google Group for updates as challenges and registration are announced.
Help shape MLM26!
Whether you have a research problem that needs ML muscle, expertise to share, or just want to get involved — we’d love to hear from you. We’re actively looking for:
- Challenge organizers — bring an ML/AI problem from your lab or organization. Learn more from our Submit a Challenge page.
- Advisors — guide a team through the program as an ML/AI or subject-matter expert
- Presenters & demo partners — showcase a tool, method, or research application to our community
- General volunteers — help facilitate sprints, workshops, and events
All roles are welcome regardless of background. Fill out the interest form by June 1 and we’ll be in touch.
What to expect
The Marathon captures the Kaggle spirit of learning by doing. Teams of up to 5 members pick a challenge and work through it together — reading docs, searching for answers, trying things, breaking them, iterating. Each challenge lists its expected prerequisites, so you can pick one that fits your current skill level. Advisors are there when you’re truly stuck, but your teammates are your primary resource. This isn’t a guided course — expect to Google a lot, struggle productively, and learn from the people next to you.
The rhythm: weekly in-person sprint sessions on Wednesday evenings, with async team work between. Participants also get hands-on cloud workshops (AWS, Google Cloud), cloud compute credits, and ML+X Nexus as a shared knowledge base across teams and cohorts. See the full schedule for session dates and workshop topics.
“Just being surrounded by machine learning enthusiasts and professionals was really inspiring and helpful.” — Graduate student, MLM25
“One of the most impactful ML events I’ve ever been a part of.” — Academic staff, MLM25
“Collaborative work with a clearly defined goal was a nice contrast to PhD research.” — Graduate student, MLM25
“Way more interesting than my classes.” — Undergraduate student, MLM25
Who should participate?
Open to anyone at or affiliated with UW–Madison — undergrads, grad students, postdocs, faculty, staff, and community members. Past participants have ranged from complete beginners to AI experts.
Minimum qualifications: To set participants up for success, we ask that all participants meet the following prerequisites.
- Python basics, machine learning fundamentals, and GitHub (enough to collaborate). If you need to get up to speed, please complete the relevant self-paced workshop(s) prior to kickoff: Intro Python, Collaborating with GitHub Desktop, and/or Intro to Machine Learning.
Find teammates: The most important thing isn’t your experience level — it’s picking a challenge in your zone of capability and finding teammates who share your pace, interests, and learning goals. For the best Marathon experience, try to form a team (max of 5) before registration opens in August. The more cohesive your team, the more you can accomplish during the Marathon. The Data Science Hub Slack is a good place to introduce yourself and find teammates over the spring and summer. Once joined, check out the #welcome channel and the #ml-community channels to get plugged into our community virtually. You may also choose to attend ML+X events throughout the semester to meet others in the community.
Thank you, sponsors!
Your support empowers Madison’s ML/AI community to tackle real‑world challenges, share hard‑won knowledge, and help one another succeed. We couldn’t do it without you.
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Interested in Sponsoring Us?
Help fuel our growing community and showcase your organization’s commitment to responsible, open ML/AI. Visit the sponsorship page to learn how your organization will be represented as a sponsor of ML+X.