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  1. evidently

    Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

    Project mention: Why Your Neural Network Fails Silently and How to Actually Debug It | dev.to | 2026-04-25

    Set up drift detection. Compare weekly distributions of model inputs against your training data baseline. Tools like Evidently make this straightforward.

  2. SaaSHub

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

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  3. eurybia

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

NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020).

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Jupyter Notebook html-report related posts

  • State of the Art data drift libraries on Python?

    3 projects | /r/mlops | 24 May 2022

  • Providing ML team with data: normalized or denormalized?

    1 project | /r/dataengineering | 20 May 2022

Index

# Project Stars
1 evidently 7,685
2 eurybia 223

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