Exploring the Azure Machine Learning service
Before we continue to set up our own development environment and do some ML, we will have a look at what was just deployed besides the main workspace, get a base understanding of all features available in the service, which we will utilize throughout the book, and have a first short look at Azure Machine Learning Studio.
Analyzing the deployed services
We will start by navigating to the Azure portal again. There, type the name of the workspace as mldemows
in the top search bar. You should see something like the result shown in Figure 3.3:
Figure 3.3 – An Azure portal search for an ML workspace
As you can see, besides the main mldemows
workspace, three other services were deployed, namely Storage account, Key vault, and Application Insights. As most of them require unique names, you will see a random alphanumeric code at the end of each name. For each one of these additional services, we can provide our...