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    ML+X Nexus: Crowdsourced ML Resources

    Nexus is the ML+X community’s centralized hub for sharing machine learning (ML) resources.

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    Website in development: The official Nexus launch date is scheduled for 7/25/24. Check back then for more substantial updates!

    What kinds of resources are hosted on Nexus?

    Any content (original or external) that can help make the practice of ML more accessible, efficient, and reproducible is welcome on the Nexus platform! This includes, but is not limited to:

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    Educational Materials (Workshops, Demos, Books, etc.): Explore a library of educational materials covering a wide range of ML-related topics, from foundational concepts to advanced techniques. Written by community members or sourced from external websites (e.g., Kaggle, YouTube), these guides offer clear explanations, practical examples, and actionable insights to help you navigate the complexities of ML with confidence.

  • 🏆 ML Stories: Discover a curated collection of blogs which dive into real-world experiences and lessons learned by ML practitioners.

  • 🚀 Exploratory Data Analysis (EDA) Case Studies: As the adage goes, “garbage in, garbage out,” emphasizing the critical role of EDA in ensuring the quality and integrity of any ML pipeline. These case studies offer firsthand experiences in navigating real-world datasets, demonstrating the technical steps and domain knowledge needed to explore different data types (time-series, tabular, images, etc.) from various fields.

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  • Coming soon! Recommendations and guides for datasets, pretrained models, and foundation models.

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