Nexus is the ML+X community’s centralized hub for sharing machine learning (ML) resources. Visit the ML+X website to learn more about the community, and join the ML+X google group to stay informed on upcoming community events!
Any content (original or external) that can help make the practice of ML 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, guides, books, videos, etc.) covering a wide range of ML-related topics, tools, and workflows, from foundational concepts to advanced techniques. These materials offer clear explanations, practical examples, and actionable insights to help you navigate the complexities of ML with confidence.
🧬 Applications & stories: Discover a curated collection of blogs, papers, and talks which dive into real-world ML applications and lessons learned by practitioners. This section also includes exploratory data analysis (EDA) case studies, which demonstrate the technical and domain knowledge needed to explore data from various fields.
🛠 Models, code, and more: Learn about popular pretrained & foundation models, useful scripts, and datasets that you can leverage for your next ML project. Learn about their features, how to use them effectively, and see examples of them in action.
This website is a team effort! We welcome and encourage fellow practitioners to contribute resources to Nexus. Learn more by visiting How to contribute.
Alternatively, check out the Applications (talks, papers, EDA case studies, etc.) or Toolbox (models, data, scripts, etc.) resources!
