Prepping data for AutoML classification
Classification, or predicting the category of something based on its attributes, is one of the key techniques of machine learning. Just like regression, you first need to prep your data before training it with AutoML. In this section, you will first navigate to your Jupyter notebook, load in your data, and transform it for use with AutoML.
Just as you loaded in your Diabetes Sample dataset via Jupyter notebooks for regression, you will do the same with the Titanic Training Data dataset. However, this time around you will do much more extensive data transformation before training your AutoML model. This is to build upon your learning; classification datasets do not necessarily require more transformation than their regression counterparts. Identical to the previous chapter, you will begin by opening up a Jupyter notebook from your compute instance.
Navigating to your Jupyter environment
Similar to Chapter 4, Building an AutoML Regression...
