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Fairness in ML Systems
Fairness has competing mathematical definitions that can't all hold at once — learn the main ones and how to choose.
- 35 min lesson
- intermediate level
- Narrated presentation
What you’ll learn
- Demographic parity
- Equalized odds & equal opportunity
- Calibration
- Impossibility theorem
- Pre/in/post-processing mitigation
- Fairness as a values choice
Inside this lesson
A narrated, slide-by-slide presentation with 1 prediction exercise, 1 knowledge check, 2 videos. You answer as you go, and the platform checks your work.