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All Projects → jphall663 → Awesome Machine Learning Interpretability

jphall663 / Awesome Machine Learning Interpretability

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A curated list of awesome machine learning interpretability resources.

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machine-learningawesomeawesome-listdata-sciencedata-mininginterpretabilitytransparencyfairnessaccountabilityinterpretable-deep-learninginterpretable-aiinterpretable-mlexplainable-mlxaifatmlinterpretable-machine-learningimlmachine-learning-interpretability

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awesome-machine-learning-interpretability Awesome

A curated, but probably biased and incomplete, list of awesome machine learning interpretability resources.

If you want to contribute to this list (and please do!) read over the contribution guidelines, send a pull request, or contact me @jpatrickhall.

An incomplete, imperfect blueprint for a more human-centered, lower-risk machine learning. The resources in this repository can be used to do many of these things today. The resources in this repository should not be considered legal compliance advice. alt-text
Image credit: H2O.ai Machine Learning Interpretability team, https://github.com/h2oai/mli-resources.

Table of Contents

Comprehensive Software Examples and Tutorials

Explainability- or Fairness-Enhancing Software Packages

Browser

Python

R

Machine learning environment management tools

Free Books

Government and Regulatory Documents

Other Interpretability and Fairness Resources and Lists

Review and General Papers

Classes

Interpretable ("Whitebox") or Fair Modeling Packages

C/C++

Python

R

AI Incident Tracker

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