This module introduces a framework for approaching fairness in machine learning, including defining and checking for fairness and considerations when choosing between different fairness implementations.
Objectives
- Provide a framework for approaching issues related to bias in data
- Provide guidance on defining and checking for fairness
- Help students identify how to choose the right technique for the application
Sections