ML System Design Interview Basics: From Notebook to Production
ML System Design Basics
System design is about how the model works in production, not just training accuracy.
What I Cover
- Data pipeline + feature store (if needed)
- Model serving (API/batch)
- Latency + cost constraints
- Monitoring: drift, accuracy drop
- Rollback strategy
