Describe data and compute services for data science and machine learning

When working with machine learning in Azure, it’s important to be familiar with the types of resources, connections, and elements that you can work with. Let’s look at each of the main types of services and resources associated with machine learning workloads.

Compute

In Azure ML, compute refers to the computing resources or power that are allocated for running machine learning jobs (such as training models or running experiments) or hosting service endpoints. This can range from serverless computing (such as functions that require a minimal amount of compute resources to execute a command) to fully deployed server clusters.

Azure ML supports various types of compute resources to cater to different needs and scenarios. Let’s take a look.

Compute cluster

This is a scalable, managed compute infrastructure that allows users to easily set up a cluster of virtual machines equipped...