Evaluating Fairness in ML
Machine Learning · Further Education · Machine Learning Ethics
This unit delves into the evaluation of fairness in machine learning systems, exploring metrics such as statistical parity, equal opportunity, and individual fairness. By the end of this unit, learners will gain a comprehensive understanding of the challenges and techniques involved in ensuring fairness in ML models.
Zum Üben gibt es 59 Aufgaben. Jede Antwort bekommt sofort eine Rückmeldung, kostenlos und ohne Anmeldung.
Das gehört dazu
- Definitions of Fairness in ML
- Statistical Parity
- Equal Opportunity
- Individual Fairness
- Disparate Impact
- Bias Mitigation Techniques
- Fairness in Practice
Stichworte
- Fairness
- Bias
- Metrics
- Mitigation Techniques