In this chapter, you learned how Amazon SageMaker Ground Truth helps you build highly accurate training datasets using image and text labeling workflows. We'll see in Chapter 5, Training Computer Vision Models, how to use image datasets labeled with Ground Truth.
Then, you learned about Amazon SageMaker Processing, a capability that helps you run your own data processing workloads on managed infrastructure: feature engineering, data validation, model evaluation, and so on.
Finally, we discussed three other AWS services (Amazon EMR, AWS Glue, and Amazon Athena), and how they could fit into your analytics and machine learning workflows.
In the next chapter, we'll start training models using the built-in machine learning models of Amazon SageMaker.