The Definitive Guide to Google Vertex AI

Implement machine learning pipelines with Google Cloud Vertex AI

Key Features

• Understand the role of an AI platform and MLOps practices in machine learning projects
• Get acquainted with Google Vertex AI tools and offerings that help accelerate the creation of end-to-end ML solutions
• Implement Vision, NLP, and recommendation-based real-world ML models on Google Cloud Platform

Book Description

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.

What you will learn

• Understand the ML lifecycle, challenges, and importance of MLOps
• Get started with ML model development quickly using Google Vertex AI
• Manage datasets, artifacts, and experiments
• Develop no-code, low-code, and custom AI solution on Google Cloud
• Implement advanced model optimization techniques and tooling
• Understand pre-built and turnkey AI solution offerings from Google
• Build and deploy custom ML models for real-world applications
• Explore the latest generative AI tools within Vertex AI

Who this book is for

If you are a machine learning practitioner who wants to learn end-to-end ML solution development on Google Cloud Platform using MLOps best practices and tools offered by Google Vertex AI, this is the book for you.

Table of Contents

1. Machine Learning project lifecycle and challenges
2. What is ML Ops and why is it important for every organization using ML?
3. It’s all about Data – Options to store and transform ML datasets
4. Vertex AI Workbench – One stop tool for all your ML Development needs
5. Training ML Models – No code option – AutoML
6. Training ML Models -Low code option – BQML
7. Training fully custom ML models with Vertex AI
8. Model Explainability through Vertex AI
9. Model optimizations – Hyper parameter tuning and NAS (TBD)
10. Vertex AI Deployment and Automation tools – Orchestration through managed Kubeflow pipelines
11. Vertex AI Governance Tools
12. Vertex AI – Generative AI Tools
13. Document AI – Customizable document processing solution
14. ML APIs – Vision API, NLP API etc.
15. Recommender Systems – Predict what movie would you like to watch?
16. Vision-Based Defect Detection System – Machines Can See Now!
17. Natural Language Models – Detecting Fake News Articles!

About the Author

Jasmeet Bhatia is a Machine Learning Architect with over 8 years of experience in Data Science and Machine Learning Engineering at Google and Microsoft, and overall has 17 years of experience in Product Engineering and Technology consulting at Deloitte, Disney, and Motorola. He has been involved in building technology solutions that focus on solving complex business problems by utilizing information and data assets. He has built high performing engineering teams, designed and built global scale AI/Machine Learning, Data Science, and Advanced analytics solutions for image recognition, natural language processing, sentiment analysis, and personalization.

Jasmeet Bhatia is an Artificial Intelligence and Machine Learning professional with 6+ years of industry experience in developing and architecting large scale AI/ML solutions using the technological advancements in the field of Machine Learning, Deep Learning, Computer Vision and Natural Language Processing. Kartik has filed 9 patents at the intersection of Machine Learning, Healthcare, and Operations. Kartik loves sharing knowledge, blogging, travel, and photography.