Summary

In this chapter, you have learned about all the prerequisites that are necessary for creating AutoML solutions in Azure. You created an AMLS workspace and accessed AML studio before creating the necessary compute to run and write your AutoML jobs. You then loaded data into a datastore and registered it as a dataset to make it available for your AutoML runs.

Importantly, you should now understand the four steps of the AutoML process: a data guardrails check, intelligent feature engineering, data transformation, and iterative ML model building. Everything you have done in this chapter will enable you to create a ML model in record time.

You are now ready for Chapter 3, Training Your First AutoML Model, where you will build your first AutoML model through a GUI. This chapter will cover a range of topics, from examining data to scoring models and explaining results. By the end of that chapter, you will not only be able to train models with AutoML, but you will also be able...