Providing ML team with data: normalized or denormalized?

This page summarizes the projects mentioned and recommended in the original post on /r/dataengineering

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  • WorkOS - The modern identity platform for B2B SaaS
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  • eurybia

    ⚓ Eurybia monitors model drift over time and securizes model deployment with data validation

    Your data scientists will cook up ugly bits of code to prepare their training data, you'll probably have to rewrite that when they want to ship to prod and also detect and handle discrepancies. In that regard, it sounds like you may enjoy Eurybia to communicate about this data with your data scientists. We made it precisely for that.

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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