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

Natural Language AI on Google Cloud

Almost every organization deals with large amounts of text data in the form of text documents, forms, contracts, PDFs, web pages, user reviews, and so on. Google Cloud offers Natural Language AI, which leverages ML models to derive insights from unstructured text data. Natural Language AI is an end-to-end product that can help in extracting, analyzing, and storing text on Google Cloud.

Google offers the following three natural language solutions:

  • AutoML for Text Analysis
  • Natural Language API
  • Healthcare Natural Language API

Let’s take a closer look at each of these solutions.

AutoML for Text Analysis

Imagine that there is an e-commerce company that receives customer queries related to a wide variety of issues, including payment failures, delivery address updates, product quality issues, and so on. As most of these queries are typed by customers in a text box, there is a need to classify these queries into a fixed...