2. Choosing a machine learning service in Azure

In the previous chapter, we learned what an end-to-end Machine Learning (ML) process looks like. We went through the different steps, from data exploration to data pre-processing, training, optimization, deployment, and operation. In this chapter, we want to find out how to best navigate through all available ML services in Azure and how to select the right one for your goal. Finally, we will explain why the Azure Machine Learning is the best choice for building custom ML models. This is the service that we will use throughout the book to implement an end-to-end ML pipeline.

First, we will take a look at the different Azure services for ML and Artificial Intelligence (AI), and discuss their differences and similarities. Some of the services will be completely managed with little flexibility, whereas other services will give you great flexibility but not everything will be managed. We will also take a look into the different...