Join us in this workshop to explore the implicit biases in real-life datasets. You’ll develop practical skills in bias detection, discovering the importance of data distribution, feature correlation and initial assumptions. Uncover the effects on prediction and discover strategies to ensure fairness and unbiased results in you machine learning models.
Prerequisites
- No coding expertise in a specific language is required but a basic understanding of programation will help.
- Bring your own laptop.
- Open to all ETH students and Student Project House community members.
About the Digital Makerspace
The Digital Makerspace is a place to grow and build your digital project within SPH.
The Digital Makerspace Managers are passionate group of makers, programmers and hackers (in the original word sense!). We love to build digital stuff and find creative solutions. We are looking forward getting to know you and build something together.
