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Explainable Ai Python Packages

Python packages with the GitHub topic explainable-ai. Sorted by relevance, with stars and monthly downloads.
interpretml
interpret-core

Fit interpretable models. Explain blackbox machine learning.

944K 7K 784
obss
sahi

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

462K 5K 746
interpretml
interpret

Fit interpretable models. Explain blackbox machine learning.

429K 7K 784
ottenbreit-data-science
aplr

APLR builds predictive, interpretable regression and classification models using Automatic Piecewise Linear Regression. It often rivals tree-based methods in predictive accuracy while offering smoother and interpretable predictions.

224K 23 5
polyaxon
traceml

Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

134K 533 47
mouradmourafiq
pandas-summary

Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

112K 533 47
polyaxon
datatile

Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

112K 533 47
jacobgil
grad-cam

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

77K 13K 2K
microsoft
raiutils

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

71K 2K 476
csinva
imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

52K 2K 138
interpretml
dice-ml

Generate Diverse Counterfactual Explanations for any machine learning model.

44K 2K 229
ModelOriented
dalex

moDel Agnostic Language for Exploration and eXplanation

40K 1K 170
mmschlk
shapiq

Shapley Interactions and Shapley Values for Machine Learning

30K 733 60
linkedin
fasttreeshap

Fast SHAP value computation for interpreting tree-based models

29K 557 37
microsoft
erroranalysis

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

26K 2K 476
microsoft
responsibleai

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

19K 2K 476
keisen
tf-keras-vis

Neural network visualization toolkit for tf.keras

9K 337 47
microsoft
raiwidgets

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

8K 2K 476
BCG-X-Official
gamma-facet

Human-explainable AI.

8K 533 46
chr5tphr
zennit

Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.

5K 243 35
11301858
xaisuite

XAISuite: Training and Explanation Generation Utilities for Machine Learning Models

5K 7 1
holistic-ai
holisticai

This is an open-source tool to assess and improve the trustworthiness of AI systems.

4K 106 31
sbobek
acfx

Actionable Counterfactual eXplanations

3K 2 1
aerdem4
lofo-importance

Leave One Feature Out Importance

3K 867 83
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