Machine Learning
Deployment Basics
Batch vs API and what to monitor.
Deployment styles
- Batch: run predictions on a schedule (CSV → CSV).
- API: serve predictions per request (FastAPI/Flask).
Monitoring
- Input drift (feature distributions change).
- Output drift (prediction distribution change).
- Latency, error rates, and data quality checks.