Throughout the Machine Learning Marathon, we use ML+X Nexus to share methods, tools, and findings—both within the marathon and with the broader UW ML/AI community. Nexus is our open-source, community-driven knowledge base, designed to preserve insights from past challenges, document widely used tools, and surface tips that help future projects hit the ground running. Our growing knowledge base includes sections for:
Workshops Notebooks ML/AI Libraries Model Guides Seminars & Forums
(and more)
Want to contribute?
We’d love for you to add to the shared knowledge pool! Whether it’s a blog, notebook, or summary of an existing ML/AI resource (e.g., dataset, library, model, etc.) every contribution makes the hackathon and ML+X community stronger—helping current teams share progress, compare strategies, and avoid reinventing the wheel. It also pays forward to future teams and to UW researchers more broadly. Nexus is used across disciplines—from biology and public health to engineering and the social sciences—by people who rely on many of the same tools and workflows you’re using here. Contributing is easier than you think: check out the guide linked below to learn more.
Participants who share a resource (blog post, notebook, tutorial, or similar) are eligible for a 50% discount/refund on their registration fee. Details are available on the registration page.