5
Lesson 5 of 20 · Learning from Examples
Data pipeline design
Production ML needs data pipelines: collection, cleaning, feature extraction, training, evaluation, and monitoring. Each step requires engineering.
- ML pipelines cover collection to monitoring.
- Each step requires careful engineering.
Think about it
What is self-supervised learning?