Summary
Organizations must drive innovation and stay agile by using emerging technologies to stay ahead of the competition. With cloud providers like AWS, these technologies are easily accessible for you to experiment with and add to your use case.
In this chapter, you began by learning about ML and AI. You learned how AWS services help build an end-to-end ML pipeline, taking an ML workload from ideation to production. You learned about three layers of AWS AI/ML services, starting with the ML infrastructure provided by AWS to train your model.
After that, you learned about Amazon SageMaker, which is at the center of the AWS ML tech stack to build, train, deploy, tune, and monitor ML models. Next, you learned about the top stack where AWS AI services reside, providing pre-trained models that can be used with simple API calls without any knowledge of ML. This AI service is available to address multiple use cases involving vision, speech, chatbots, forecasting, and recommendations...
