PyPI Stats
  • Insights
  • PyPI
  • GitHub
  • Search
  • Compare
  • Advisories
  • Ecosystem
  • About
Home

Interpretability Python Packages

Python packages with the GitHub topic interpretability. Sorted by relevance, with stars and monthly downloads.
shap
shap

A game theoretic approach to explain the output of any machine learning model.

14.5M 25K 4K
interpretml
interpret-core

Fit interpretable models. Explain blackbox machine learning.

955K 7K 783
tensorflow
tensorflow-decision-forests

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

649K 693 116
google
ydf

A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.

537K 652 78
pytorch
captum

Model interpretability and understanding for PyTorch

495K 6K 557
interpretml
interpret

Fit interpretable models. Explain blackbox machine learning.

398K 7K 783
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.

228K 23 5
jacobgil
grad-cam

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

82K 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.

72K 2K 476
csinva
imodels

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

52K 2K 138
ndif-team
nnsight

The nnsight package enables interpreting and manipulating the internals of deep learned models.

47K 917 87
ModelOriented
dalex

moDel Agnostic Language for Exploration and eXplanation

37K 1K 170
SeldonIO
alibi

Algorithms for explaining machine learning models

31K 3K 264
linkedin
fasttreeshap

Fast SHAP value computation for interpreting tree-based models

30K 555 38
mmschlk
shapiq

Shapley Interactions and Shapley Values for Machine Learning

27K 722 58
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.

21K 2K 476
iancovert
sage-importance

For calculating global feature importance using Shapley values.

16K 287 33
frgfm
torchcam

Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)

16K 2K 224
yohanpoul
etzchaim

A diagnosable brain for your LLM. Cognitive architecture in the SOAR/ACT-R/CLARION/LIDA lineage, for the LLM era. Apache 2.0.

11K 1 0
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.

9K 2K 476
MAIF
shapash

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

8K 3K 383
a9lim
saklas

Activation steering and trait monitoring for HuggingFace transformers

8K 3 0
BCG-X-Official
gamma-facet

Human-explainable AI.

7K 532 46
    • Data from PyPI, GitHub, ClickHouse, and BigQuery