Book Image

The Definitive Guide to Google Vertex AI

By : Jasmeet Bhatia, Kartik Chaudhary
4 (1)
Book Image

The Definitive Guide to Google Vertex AI

4 (1)
By: Jasmeet Bhatia, Kartik Chaudhary

Overview of this book

While AI has become an integral part of every organization today, the development of large-scale ML solutions and management of complex ML workflows in production continue to pose challenges for many. Google’s unified data and AI platform, Vertex AI, directly addresses these challenges with its array of MLOPs tools designed for overall workflow management. This book is a comprehensive guide that lets you explore Google Vertex AI’s easy-to-advanced level features for end-to-end ML solution development. Throughout this book, you’ll discover how Vertex AI empowers you by providing essential tools for critical tasks, including data management, model building, large-scale experimentations, metadata logging, model deployments, and monitoring. You’ll learn how to harness the full potential of Vertex AI for developing and deploying no-code, low-code, or fully customized ML solutions. This book takes a hands-on approach to developing u deploying some real-world ML solutions on Google Cloud, leveraging key technologies such as Vision, NLP, generative AI, and recommendation systems. Additionally, this book covers pre-built and turnkey solution offerings as well as guidance on seamlessly integrating them into your ML workflows. By the end of this book, you’ll have the confidence to develop and deploy large-scale production-grade ML solutions using the MLOps tooling and best practices from Google.
Table of Contents (24 chapters)
1
Part 1:The Importance of MLOps in a Real-World ML Deployment
4
Part 2: Machine Learning Tools for Custom Models on Google Cloud
14
Part 3: Prebuilt/Turnkey ML Solutions Available in GCP
18
Part 4: Building Real-World ML Solutions with Google Cloud

Importing data to use with Vertex AI AutoML

The first step when planning to use the Vertex AI AutoML feature is to import the data you plan to use to train as Vertex AI datasets:

  1. Navigate to Vertex AI | Datasets within the Google Cloud console, and click Create to start creating a new Vertex AI dataset.
Figure 5.1 – Creating a Vertex AI dataset

Figure 5.1 – Creating a Vertex AI dataset

  1. Type in the name of the dataset, select Tabular as the data type, choose Regression/classification, and then click CREATE.
Figure 5.2 – Selecting a dataset type and model objective

Figure 5.2 – Selecting a dataset type and model objective

  1. Upload the file named hotel_reservation_data.csv that you previously downloaded from the GitHub repository.

Figure 5.3 – Specifying a data source

  1. Enter a path to the GCS location where you would like to store the imported file. If you have not created a GCS bucket before, click on Browse and type in a name for the storage...