Overview
The goal is to understand how uncertainty behaves across predictions and how to convert it into simple decisions: automate, guide the user, or escalate.
AI / ML Project
Uncertainty Metrics Lab
Hands-on lab exploring practical uncertainty signals for multiclass classification: confidence, entropy, and ensemble disagreement.
GitHub RepoMulticlass classification
What’s inside
- Top-1 confidence
- Normalized entropy
- Ensemble disagreement
- Operational decision policy
Why it matters
In real systems, raw predictions are not enough. This lab helps translate model uncertainty into practical product decisions, making AI behavior easier to trust, monitor, and improve.