Summary

In this chapter, you learned how to get started with Google Cloud AI Platform and learned about AI Hub, how to build a notebook instance, and how to run a simple program. You also learned about the different flavors of automated ML offered by GCP, including AutoML Natural Language, AutoML Tables, AutoML Translation, AutoML Video, and AutoML Vision. If the breadth of GCP offerings, capabilities, and services have left you overwhelmed, you are in good company.

In the next chapter, we will do a deep dive into Google Cloud AutoML Tables. We will build models and explain how the automated ML functionality works with AutoML Tables, that is, how you can take unstructured data and perform automated ML tasks of analyzing the input features (feature engineering), selecting the model (neural architecture search), and doing hyperparameter tuning. We will deploy these models on GCP and test them via web services to demonstrate the operationalization of these capabilities. Stay tuned...