Summary
AI and machine learning may have captured the world's imagination, but there's a large gap between the pie-in-the-sky promises of AI and the reality of AI projects. Machine learning projects, in particular, fail often and slowly. Traditional managers treat data science projects like software engineering projects, and data scientists work in a manual, time-consuming manner. Luckily, AutoML has emerged as a way to speed up projects, and Microsoft has created its AutoML offering with your needs in mind.
You are now primed for Chapter 2, Getting Started with Azure Machine Learning Service, which will introduce you to the Microsoft Azure Machine Learning workspace. You will create an Azure Machine Learning workspace and all of the necessary components required to start an AutoML project. By the end of the chapter, you will have a firm grasp of all of the different components of Azure Machine Learning Studio and how they interact.