Lecture 16
May 23, 2019
Overview
Overview
- ML pipeline review
- Training and optimization review
- Model update process
- Model availability after training
- Deployment Methods
- Serving as inference
- Updating model and parameters
- Mixed models
- Method comparison
Lecture Video
Lecture Video
Resources
Resources
- Slides [Link]