Chapter 12: Using BigQuery ML with AI Notebooks
For data scientists and machine learning engineers, notebooks are a fundamental productivity tool. Notebooks allow us to interact with computing resources because we can use them to write and execute code, visualize the results, and share the outcomes with other data scientists. Data engineers, data scientists, and machine learning engineers make experiments and explore data before deploying code into the production environment. They leverage notebooks because they offer a flexible and agile environment to develop and test in.
In this chapter, we'll learn what AI Platform Notebooks is, how to provision a notebook environment, and how to use it to develop a BigQuery ML model.
We'll start by discovering ...
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