Exercise – using GCP in AutoML to train an ML model
As we learned earlier in this chapter, AutoML is an automated way for you to build an ML model. It will handle the model selection, hyperparameter tuning, and various data preparation steps. Specifically for the data preparation part, it will not be smart enough to transform data from very raw tables and automatically create clean features. What AutoML will do, however, is perform simple data preparation tasks, such as detecting numeric, binary, categorical, and text features, and then apply the required transformation to be used in the ML training process. Let's learn how to do this. Here are the steps that you will complete in this exercise:
- Create Vertex AI datasets.
- Set up the AutoML training.
For the use case and dataset, we will use the credit card default dataset from our previous exercise. First, go to your GCP console and find and click Vertex AI. If you haven't enabled the API, there will...
