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aif360

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

adversarial-robustness-toolbox

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

aix360

Interpretability and explainability of data and machine learning models

versatile-evasion-attacks

Security protocols for estimating adversarial robustness of machine learning models for both tabular and image datasets. This package implements a set of evasion attacks based on metaheuristic optimization algorithms, and complex cost functions to give reliable results for tabular problems.

uq360

Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.

universal-evasion-attacks

Security protocols for estimating adversarial robustness of machine learning models for both tabular and image datasets. This package implements a set of evasion attacks based on metaheuristic optimization algorithms, and complex cost functions to give reliable results for tabular problems.

aif360-fork2

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.