Describe model management and deployment capabilities in Azure ML
As you’ve already seen throughout this chapter, Azure ML has a lot of capabilities –ranging from developing to deploying both simple and complex machine learning models.
In this section, we’ll look at three different (yet connected) areas of model management in Azure ML:
- Model management
- Model deployment capabilities
- Machine learning operations
Let’s look at each of them.
Model management and deployment capabilities
Azure ML offers robust model deployment capabilities, allowing data scientists and developers to operationalize their machine learning models efficiently and at scale. These capabilities span various deployment targets, including cloud, on-premises, and edge environments, and provide the flexibility to meet a wide range of operational requirements.
Over the next few pages, we’ll look at the key deployment capabilities of Azure ML.
