/ml-fairness-advanced-feb2022

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

Primary LanguageJupyter NotebookOtherNOASSERTION

A Deep Dive into Fairness in Machine Learning

Level: Advanced

Presentation: fairness advanced

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

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 4.0