In Need of Guidance: Implementing MLOps in a Complex Organization as a Junior Data Engineer

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

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  • metaflow

    :rocket: Build and manage real-life ML, AI, and data science projects with ease!

  • feast

    Feature Store for Machine Learning

  • A feature store usually stores features which are used for training ML model. It is a centralized place for collaboration between data engineer, ML engineer, and data scientist, so that data engineer can write to the feature store while ML engineer and data scientist read from it. Hopsworks https://www.hopsworks.ai and feast https://github.com/feast-dev/feast are examples of open source feature store.

  • 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.

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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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