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

What is BQML?

BQML is a powerful, built-in ML service provided by Google Cloud that allows users to create, train, and deploy ML models using familiar SQL queries. BQML is designed to simplify the process of building and deploying ML models for those who may not have a strong background in data science or programming. In this chapter, we will explore the key features and capabilities of BQML and how you can use it to leverage the power of Google Cloud AI for your projects.

BQML provides a seamless way to integrate ML into your data analytics workflows without requiring a deep understanding of ML concepts or programming languages. With BQML, you can do the following:

  • Create and train ML models using SQL queries
  • Make predictions using trained models
  • Evaluate the performance of your models
  • Perform feature transformation and hyperparameter tuning
  • Understand model explanations and weights
  • Export and import models

Utilizing BQML offers numerous advantages...