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

Speech AI on Google Cloud

Another important form of capturing and storing information is speech. Google has done decades of research to come up with state-of-the-art solutions for many speech and audio data-related use cases. A significant amount of critical information is present in the forms of audio calls and recorded messages and thus it becomes important to transcribe and extract useful insights from them. Also, there are voice assistant-related use cases that demand text-to-speech kind of functionality. Google Cloud offers several solutions for speech understanding and transcriptions. To help organizations tackle these use cases, Google has created the following product offerings related to speech data:

  • Speech-to-Text
  • Text-to-Speech

Now, let’s learn about each of them in detail.

Speech-to-Text

A good chunk of useful data is present in unstructured form, such as audio recordings, customer voice calls, videos, and so on, for many organizations. Thus...