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https://github.com/pyladiesams/ml-fairness-advanced-feb2022

Learn different techniques for mitigating fairness-related harms using Fairlearn.
https://github.com/pyladiesams/ml-fairness-advanced-feb2022

fairlearn fairness fairness-ml ml workshop

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Learn different techniques for mitigating fairness-related harms using Fairlearn.

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# A Deep Dive into Fairness in Machine Learning
### Level: Advanced
### Presentation: [fairness advanced](workshop/fairnessadvanced.pdf)

## Workshop description
In the past few years there has been an increasing awareness amongst both the public and scientific community that algorithmic systems can reproduce, amplify, or even introduce unfairness in our societies. During this workshop, you will learn how to use and critically examine fairness-aware machine learning techniques.

## Requirements
- python >= 3.6
- conda, venv, pyenv
- jupyter notebook or jupyter lab

## Usage
Set up a Python environment that can run Jupyter notebooks (Jupyter or Jupyterlab) (see Requirements section).

1. Clone the repository
2. Install the required libraries with pip: `pip install -r requirements.txt`
3. Start jupyter(lab) and navigate to the workshop folder

## Video record
Re-watch YouTube stream [here](https://www.youtube.com/watch?v=2fVs8T8cGBg)

## Credits
This workshop was set up by @pyladiesams and @hildeweerts

This work is licensed under a
[Creative Commons Attribution-NonCommercial 4.0 International License][cc-by-nc].

[![CC BY-NC 4.0][cc-by-nc-image]][cc-by-nc]

[cc-by-nc]: http://creativecommons.org/licenses/by-nc/4.0/
[cc-by-nc-image]: https://licensebuttons.net/l/by-nc/4.0/88x31.png
[cc-by-nc-shield]: https://img.shields.io/badge/License-CC%20BY--NC%204.0-lightgrey.svg