Summary

In this chapter, you learned about the AWS ML stack and how to get started with AWS SageMaker and notebook development. You also became acquainted with SageMaker Autopilot and its automated ML workflow capabilities. We provided you with an overview of the built-in algorithms, the SageMaker ML life cycle, and what algorithms and techniques are used by SageMaker automated ML. This introduction gives you the background knowledge needed for further exploration and learning of the AWS ML stack and the SageMaker automated ML life cycle.

In the next chapter, we will use some of the SageMaker Autopilot features practically to run classification, regression, and time series analysis.