Preparing data for AutoML regression

Before you can train any model with AutoML, you must have a properly cleansed dataset. This section will walk you through how to prepare data for any AutoML regression solution. You will begin by using your compute instance to access Jupyter notebook, a code editor that will let you code in Python. Following that, you will cleanse, transform, and register your data as an Azure dataset. This will give you a dataset that's ready for training in the next section.

Some of you may be new to Python or even to coding in general, but don't worry. While scripting an AutoML solution may seem much more difficult than using the GUI, in reality, it's a matter of making slight changes to boilerplate code.

Using the code found in this book's GitHub repository, you only have to alter it slightly to adapt it to your own custom solution using your own custom data. Furthermore, for this exercise, you've already completed most of the...