"As Cloud-like as Possible" Data Science: Local MLOps with Docker Compose

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  1. acap-datasci-env

    Discontinued "As Cloud-like as Possible" Data Science Environment [GET https://api.github.com/repos/m15a/acap-datasci-env: 404 - Not Found // See: https://docs.github.com/rest/repos/repos#get-a-repository]

    Detailed prerequisite steps, such as setting environment variables, are written in the GitHub README.

  2. SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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  3. versitygw

    A simple to deploy but feature rich S3 object storage server for your filesystem

    Data store: Versity S3 Gateway emulates S3 storage.

  4. MLflow

    The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.

    Experiment management: MLflow tracks models, parameters, and results.

  5. marimo

    A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.

    Notebook: Marimo for interactive development.

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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