If you haven't created Azure Machine Learning Workspace yet, first run configuration notebook. If you created a Workspace from Azure portal and launched notebooks from there, your workspace is configured already, and you can proceed to examples.
Then move to more comprehensive examples in tutorials folder, or explore different features in how-to-use-azureml folder.
Important: You must select Python 3.6 as the kernel for your notebooks to use the SDK.
Note: The config.json file in this folder was created for you with details of your Azure Machine Learning service workspace. Both these notebooks use this file to connect to your workspace. You can also copy this file into other places where you have code that needs this connection.