Chapter 7: Working with SageMaker Feature Store, SageMaker Clarify, and SageMaker Model Monitor
In the previous chapter, we had our first look at SageMaker Studio, along with its automated machine learning capabilities, by using SageMaker Autopilot and Automatic Model Tuning to prepare high-quality models. In this chapter, we will focus on a few more capabilities of SageMaker that have great integration with SageMaker Studio – SageMaker Feature Store, SageMaker Clarify, and SageMaker Model Monitor. These capabilities help data scientists and machine learning practitioners handle specific but relevant requirements when working on production-level machine learning experiments and deployments.
These include using online and offline feature stores, detecting bias in the data, enabling machine learning explainability, and monitoring the deployed model. The following diagram shows how these capabilities are used in the different stages of the machine learning process:
