Continuous training pipeline — what triggers retraining?
mediumAnswer
- (1) Schedule (nightly / weekly).
- (2) New data threshold (X labeled examples).
- (3) Drift alert (PSI / MMD breach).
- (4) Performance degradation (accuracy drop on rolling holdout).
- (5) Manual trigger.
- (6) Upstream data change (new source available).
- Each trigger creates run → train → evaluate → guardrail check → auto-deploy or human review.
- Google TFX / Kubeflow implementation patterns.
- Anti-pattern: retrain-on-any-drift → wasted compute + noisy models.
- Filter triggers carefully.
Check yourself — multiple choice
- Just schedule
- Schedule + new data threshold + drift alert + perf degradation + manual + upstream change; each → train → eval → guardrail → auto-deploy/review; filter carefully, not every drift
- Random
- Not real
CT triggers: schedule + data + drift + perf + manual + upstream; filter.
#mlops#pipeline
Practise MLOps & Data Quality
215 interview questions in this topic.