PyPI · npm
Arize-ai/phoenix
AI Observability & Evaluation
Custom licenseAug 28, 2026 · metrics 2.10.0
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#explainability
Every repository in the public record carrying this tag — from its GitHub topics or the keywords its package registries publish. Health is measured under the same versioned methodology as the rest of the record.
7 records
PyPI · npm
shap/shap
A game theoretic approach to explain the output of any machine learning model.
MITAug 5, 2026 · metrics 2.10.0
PyPI
mmschlk/shapiq
Shapley Interactions and Shapley Values for Machine Learning
MITJul 26, 2026 · metrics 2.10.0
npm · PyPI
interpretml/interpret
Fit interpretable models. Explain blackbox machine learning.
MITAug 12, 2026 · metrics 2.10.0
PyPI
GiacomoSaccaggi/scomp_link
End-to-end ML toolkit automating the complete workflow — data profiling, preprocessing, feature engineering, model selection, training, validation, explainability, drift monitoring, fairness checks, and interactive HTML reporting. Includes a full CLI for zero-code ML pipelines. Python 3.10+.
MITJul 16, 2026 · metrics 2.10.0
PyPI
Arize-ai/client_python
A Python client to interact with Arize API
Apache-2.0Jul 28, 2026 · metrics 2.10.0
PyPI
givasile/effector
Effector - a Python package for global and regional effect methods
MITJul 17, 2026 · metrics 2.10.0