Bea Stollnitz - Choosing the compute for Azure ML resources

When training a machine learning model or deploying it to an endpoint, you'll need to choose an appropriate machine to run it. I'll use the term "compute" to refer to the virtual machine (or set of machines) that runs your code in the cloud. The goal of this blog post is to give you an overview of all the compute options available to you in Azure ML, so that you can choose an appropriate option for your scenario. I'll assume that you're already familiar with the basic concepts of Azure ML, and that you have some experience using it for your own projects. Throughout this post, I'll discuss the following three major compute types available in Azure ML: I'll also briefly mention the available VM sizes, including how to get more quota for a particular VM size.