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 Document AI?

Document AI is an end-to-end AI-based solution for extracting and classifying useful information from any kind of unstructured documents, including scanned images, PDFs, forms, emails, and contracts. Document AI’s solution includes pre-trained ML models for extraction and other document-related tasks, and it also provides the flexibility to uptrain existing models and train custom models without writing much code. Document AI is one unified solution that can help businesses manage the entire unstructured document life cycle, ensuring a high level of accuracy and low costs to accelerate deployment to meet customer expectations.

Some key features of Google Cloud’s Document AI platform are as follows:

  • Google’s state-of-the-art AI: The Document AI platform is built upon Google’s industry-leading AI innovations in various fields, including computer vision (including OCR), NLP, and semantic search, to make this platform highly accurate...