Fairness

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.

AI Fairness 360Python

An extensible open-source toolkit for detecting, mitigating, and explaining bias in machine learning datasets and models.

Awesome Decision Tree PapersPython

A curated collection of research papers on decision, classification, and regression trees with implementations from top ML conferences.

dalexPython

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

aequitasPython

An open-source toolkit for auditing bias and experimenting with fairness methods in machine learning models.

FairMLPython

A Python toolbox for auditing machine learning models to detect and quantify bias in black-box predictions.

Awesome Fairness in AI

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

LiFTScala

A Scala/Spark library for measuring fairness and mitigating bias in large-scale machine learning workflows.

themis-mlJupyter Notebook

A Python library implementing fairness-aware machine learning algorithms for measuring and mitigating discrimination in predictive models.

REVISE: REvealing VIsual biaSEsJupyter Notebook

A tool for automatically detecting and suggesting mitigation for object, attribute, and geography-based biases in visual datasets.

MCGradJupyter Notebook

A scalable Python tool for multicalibration that ensures ML model predictions are well-calibrated across all data segments, not just globally.