Summary

You have now implemented a fully automated ML batch scoring solution using an AutoML trained model. You've created pipelines that can score models, pipelines that can process big data in parallel, and pipelines that can retrain AutoML models. You can trigger them whenever you want and you can even set up an automated scoring schedule. This is no small feat, as many organizations have spent years trying to learn best practices for these tasks.

In Chapter 10, Creating End-to-End AutoML Solutions, you will cement your knowledge as you learn how to ingest data into Azure, score it with ML pipelines, and write your results to whatever location you want.