interpretml / interpret
Fit interpretable models. Explain blackbox machine learning.
Why this job: topics: scikit-learn, gradient-boosting, machine-learning
What it does
InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions.
Get started
pip install interpret
# OR
conda install -c conda-forge interpret- Maintenance
- Active
- Last commit 4 days ago
- Stars
- 6,978
- +5 this week
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.7.8
- Released 8 months ago
- Built with
- C++
- 57% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 93% closed
- 36 still open
- Pull requests
- 153 merged
- 11 waiting
- Releases
- 66
- 5 in the last year
- Contributing guide (opens in new tab)
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- C++ 57%
- Python 38%
- Shell 2%
- C 1%
Topics
- machine-learning
- interpretability
- gradient-boosting
- blackbox
- scikit-learn
- xai
- interpretml
- interpretable-machine-learning
- interpretable-ai
- transparency
- iml
- interpretable-ml
Project record
- JobAI libraries and models
- StatusListed
- Commits3,992
- Forks801
- Watching141
- Stars in 28 days+21
- CreatedMay 3, 2019
- First seen by usNov 7, 2026
- CheckedNov 10, 2026