Chapter 2: Introducing Amazon SageMaker Studio
As we just learned in Chapter 1, Machine Learning and Its Life Cycle in the Cloud, an ML life cycle is complex and iterative. Steps can be quite manual even though most things are done with coding. Having the right tool for an ML project is essential for you to be successful in delivering ML models for production in the cloud. With this chapter, you are in the right place! Amazon SageMaker Studio is a purpose-built ML Integrated Development Environment (IDE) that offers features covering an end-to-end ML life cycle to make developers' and data scientists' jobs easy in the AWS Cloud.
In this chapter, we will cover the following:
- Introducing SageMaker Studio and its components
- Setting up SageMaker ...
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