PyPI · npm
Arize-ai/phoenix
AI Observability & Evaluation
Eigene Lizenz28. Aug. 2026 · Metriken 2.10.0
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#explainability
Alle Repositories im öffentlichen Register, die dieses Tag tragen — aus ihren GitHub-Topics oder den von ihren Paket-Registries veröffentlichten Schlagwörtern. Die Gesundheit wird nach derselben versionierten Methodik gemessen wie im übrigen Register.
9 Einträge
PyPI · npm
shap/shap
A game theoretic approach to explain the output of any machine learning model.
MIT16. Sept. 2026 · Metriken 2.10.0
PyPI
mmschlk/shapiq
Shapley Interactions and Shapley Values for Machine Learning
MIT14. Sept. 2026 · Metriken 2.10.0
PyPI · npm
interpretml/interpret
Fit interpretable models. Explain blackbox machine learning.
MIT17. Sept. 2026 · Metriken 2.10.0
PyPI
CodeBoarding/CodeBoarding
Interactive architecture diagrams for codebases
MIT20. Sept. 2026 · Metriken 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+.
MIT9. Sept. 2026 · Metriken 2.10.0
PyPI
Arize-ai/client_python
A Python client to interact with Arize API
Apache-2.014. Sept. 2026 · Metriken 2.10.0
PyPI
givasile/effector
Effector - a Python package for global and regional effect methods
MIT10. Sept. 2026 · Metriken 2.10.0
PyPI
solvi-ai/solvi
A runtime where decision models propose and your code decides: typed questions, hard rules, quotes checked against the text, escalation with a guaranteed error budget, replayable traces. Works with any System One model.
Apache-2.011. Okt. 2026 · Metriken 2.10.0