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fairmlaudits's Introduction

FairMLAudits

A comprehensive professionally curated resource on Fairness Auditing of ML models including the best tutorials, videos, books, papers, articles, courses, websites, conferences and open-source libraries code in Python.

I have created this resource while completing my PhD in Fair Machine Learning with the NoBias ITN Network. The resources were meticulously collected since 2020 and after completing my PhD. I have decided to share them with the global machine learning community.

The goal of this repository is a curated list of resources that serve specifically to evaluate and measure fairness in ML models

What is a Fair ML Audit

Regulation

Tutorials

  1. [Dealing with Bias and Fairness in Data Science Systems: A Practical Hands-on Tutorial](https://link-url-here.org](https://www.youtube.com/watch?v=N67pE1AF5cM&ab_channel=DataScienceforSocialGood) AAAI 2021, KDD 2020,Pedro Saleiro, Feedzai, Kit T. Rodolfa, Carnegie Mellon University, Rayid Ghani, Carnegie Mellon University

Papers

Use Cases

Videos

Books

Presentation slides

Researchers

Conferences and workshops

Authors and contributors

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