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https://github.com/pyladiesams/ml-fairness-beginner-nov2021

Assess fairness of machine learning models and choose an appropriate fairness metric for your use case with Fairlearn
https://github.com/pyladiesams/ml-fairness-beginner-nov2021

fairlearn fairness fairness-ml ml workshop

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Assess fairness of machine learning models and choose an appropriate fairness metric for your use case with Fairlearn

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# An Introduction to Fairness in Machine Learning using Fairlearn
### Level: Beginner
### Presentation: [introduction to fairness](workshop/fairnessbeginner.pptx)

## 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 the workshop, you will learn how to assess the fairness of machine learning models and how to choose an appropriate fairness metric for your use case.

## Requirements
- python >= 3.6
- 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://youtu.be/es5nT7Qhj-w)

## 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