A Python package to assess and improve fairness of machine learning models.

😎 Everything about class-imbalanced/long-tail learning: papers, codes, frameworks, and libraries | 有ゆう关类别不平衡へいこう/长尾学がく习的一切いっさい：论文、代だい码、框かまち架か与あずか库

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.

A library for generating and evaluating synthetic tabular data for privacy, fairness and data augmentation.

Tensorflow's Fairness Evaluation and Visualization Toolkit

Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency

Fair Resource Allocation in Federated Learning (ICLR '20)

WEFE: The Word Embeddings Fairness Evaluation Framework. WEFE is a framework that standardizes the bias measurement and mitigation in Word Embeddings models. Please feel welcome to open an issue in case you have any questions or a pull request if you want to contribute to the project!

The LinkedIn Fairness Toolkit (LiFT) is a Scala/Spark library that enables the measurement of fairness in large scale machine learning workflows.

Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584

Code accompanying our papers on the "Generative Distributional Control" framework

Train Gradient Boosting models that are both high-performance *and* Fair!

Toolkit for Auditing and Mitigating Bias and Fairness of Machine Learning Systems 🔎🤖🧰

Flexible tool for bias detection, visualization, and mitigation

A Python toolkit for analyzing machine learning models and datasets.

FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)

Fairness Aware Machine Learning. Bias detection and mitigation for datasets and models.

Papers and online resources related to machine learning fairness

Dataset associated with "BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation" paper

Tilted Empirical Risk Minimization (ICLR '21)