More than just a repository of content from across the internet, ML+X Nexus is a curated, community-driven platform that captures the collective knowledge and experiences of ML+X (and the broader UW campus). It serves as a growing knowledge hub—preserving past discussions, highlighting widely used tools and datasets, and evolving alongside our community’s needs.
Any content (original or external) that can help make the practice of ML/AI more connected, accessible, efficient, and reproducible is welcome on the Nexus platform! This includes, but is not limited to…
🧠 Educational materials: Explore a library of educational materials (workshops, books, videos, etc.) covering a wide range of ML-related topics, tools, and workflows, from foundational concepts to advanced techniques.
🛠 Models, code, and more: Learn about popular models, tools, and datasets that you can leverage for your next ML project.
🧬 Applications & stories: Discover a curated collection of blogs, papers, and talks which dive into real-world ML applications and lessons learned by practitioners.
Disclaimer: The crowdsourced resources on this website are not endorsed by the UW-Madison and have not been vetted by the Division of Information Technology.
To narrow down your search, select one of the general category groupings from the left sidebar (e.g., Learn, Applications, Toolbox). You can also select one of the category tags on the right sidebar to filter resources. Visit the Category glossary if you are unsure about the meaning of any of these tags.
