Summary

In this chapter, you reviewed the basic capabilities of Amazon SageMaker Feature Store along with the APIs to use. By combining different capabilities, you learned how to reuse engineered features across training and inference phases of a single machine learning project and across multiple ML projects. Finally, you combined streaming ingestion and serving to design near real-time inference solutions. In the next chapter, you will use these engineered features to train and tune machine learning models at scale.