Chapter 10: Advanced Training Techniques
In the previous chapter, you learned when and how to scale training jobs using features such as Pipe mode and distributed training, as well as alternatives to S3 for dataset storage.
In this chapter, we'll conclude our exploration of training techniques. In the first part of the chapter, you'll learn how to slash down your training costs with managed spot training, how to squeeze every drop of accuracy from your models with automatic model tuning, and how to crack models open with SageMaker Debugger.
In the second part of the chapter, we'll introduce two new SageMaker capabilities that help you build more efficient workflows and higher quality models: SageMaker Feature Store and SageMaker Clarify.
This chapter covers the following topics:
- Optimizing training costs with managed spot training
- Optimizing hyperparameters with automatic model tuning
- Exploring models with SageMaker Debugger
- Managing features...
