Summary

In this chapter, we looked at how AI/ML technologies play a big role in predictive analytics so that organizations can stay ahead of the curve and proactively make decisions before things happen. But at the same time, we also looked at many of the barriers related to the adoption of AI/ML and how AWS is able to overcome all these barriers.

We introduced the different stacks of how AWS provides services specific to each of these layers. For the AI layer, AWS provides a long list of 20+ services that help with specific types of AI problems such as speech, image, text, and so forth. These services help fast-track solutions that can be solved by pre-trained ML models.

We then looked at Amazon SageMaker as an ML service that has many components to it. SageMaker Canvas helps business analysts with low-code/no-code types of tools so that they can quickly create ML models and predict business outcomes. We looked at how SageMaker Studio has various tools inside it to help with...