Xai

InterpretMLC++

An open-source Python package for training interpretable glassbox models and explaining blackbox machine learning systems.

Awesome Machine Learning Interpretability

A curated list of practical resources for responsible machine learning, covering interpretability, governance, safety, and ethics.

AlibiPython

A Python library for explaining machine learning models using black-box, white-box, local, and global interpretation methods.

AI Explainability 360Python

An open-source Python toolkit providing a comprehensive collection of algorithms for interpreting and explaining machine learning models and datasets.

Awesome Explainable AIMarkdown

A curated collection of research papers, books, courses, and Python libraries for explainable AI (XAI) and machine learning interpretability.

dalexPython

A model-agnostic toolkit for exploring and explaining the behavior of complex machine learning models in R and Python.

xaiPython

A Python toolbox for explainable AI, providing tools for data analysis, model evaluation, and bias mitigation in machine learning.

anchorJupyter Notebook

A model-agnostic method for generating high-precision rule-based explanations for black-box classifier predictions.

PySS3Python

A Python library for interpretable text classification using the SS3 model, with built-in visualization tools for explainable AI.

Awesome Fairness in AI

A curated list of resources for understanding, measuring, and mitigating fairness issues in artificial intelligence and machine learning systems.

XAI

A curated collection of papers, methods, critiques, and resources for Explainable AI (XAI) and Interpretable Machine Learning.