Skip to main content
Pre-Alpha
This lesson is in the pre-alpha phase, which means that it is in early development, but has not yet been taught.
Light
Dark
Auto
Instructor View
Learner View
Menu
Trustworthy AI: Explainability, Bias, Fairness, and Safety
Trustworthy AI: Explainability, Bias, Fairness, and Safety
Key Points
Instructor Notes
Extract All Images
More
Reference
Search the All In One page
Trustworthy AI: Explainability, Bias, Fairness, and Safety
Toggle Theme
Light
Dark
Auto
Instructor View
Learner View
EPISODES
Summary and Schedule
1. Overview
2. Preparing to train a model
3. Model evaluation and fairness
4. Model fairness: hands-on
5. Interpretablility versus explainability
6. Explainability methods overview
7. Explainability methods: deep dive
8. Explainability methods: linear probe
9. Explainability methods: GradCAM
10. Estimating model uncertainty
11. OOD detection: overview, output-based methods
12. OOD detection: distance-based and contrastive learning
13. OOD detection: training-time regularization
14. Documenting and releasing a model
RESOURCES
Key Points
Instructor Notes
Extract All Images
Reference
See all in one page
Learner Profiles
This is a placeholder file. Please add content here.
Back
To Top