ML Observability & Drift
Feature and prediction monitoring, delayed labels, drift statistics, and alerting that does not cry wolf.
5concepts
64flashcards
36minutes of reading
- 01 Prediction Logging and Traceability What to record at inference so that a question asked three months later has an answer, why the feature vector matters more than the input, and the sampling and privacy tradeoffs.
- 02 The Three Drifts and How They Differ Covariate shift, label shift and concept drift decomposed precisely, why only one of them necessarily degrades a model, and which of them your monitoring can actually see.