You're reading from Google Machine Learning and Generative AI for Solutions Architects Build efficient and scalable AI/ML solutions on Google Cloud

Product type Paperback

Published in Jun 2024

Publisher Packt

ISBN-13 9781803245270

Length 552 pages

Edition 1st Edition

Languages

Gen

Tools

Google Cloud Platform

Concepts

Machine Learning

Author (1):

Kieran Kavanagh

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Table of Contents (24) Chapters

Preface

1. Part 1:The Basics FREE CHAPTER

2. Chapter 1: AI/ML Concepts, Real-World Applications, and Challenges

3. Chapter 2: Understanding the ML Model Development Life Cycle

4. Chapter 3: AI/ML Tooling and the Google Cloud AI/ML Landscape

5. Part 2:Diving in and building AI/ML solutions

6. Chapter 4: Utilizing Google Cloud’s High-Level AI Services

7. Chapter 5: Building Custom ML Models on Google Cloud

8. Chapter 6: Diving Deeper – Preparing and Processing Data for AI/ML Workloads on Google Cloud

9. Chapter 7: Feature Engineering and Dimensionality Reduction

10. Chapter 8: Hyperparameters and Optimization

11. Chapter 9: Neural Networks and Deep Learning

12. Chapter 10: Deploying, Monitoring, and Scaling in Production

13. Chapter 11: Machine Learning Engineering and MLOps with Google Cloud

14. Chapter 12: Bias, Explainability, Fairness, and Lineage

15. Chapter 13: ML Governance and the Google Cloud Architecture Framework

16. Chapter 14: Additional AI/ML Tools, Frameworks, and Considerations

17. Part 3:Generative AI

18. Chapter 15: Introduction to Generative AI

19. Chapter 16: Advanced Generative AI Concepts and Use Cases

20. Chapter 17: Generative AI on Google Cloud

21. Chapter 18: Bringing It All Together: Building ML Solutions with Google Cloud and Vertex AI

22. Index

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Overview of generative AI in Google Cloud

The pace of generative AI development in Google Cloud is nothing short of astonishing. It seems like almost every day, a new model version, service, or feature is announced. In this section, I’ll introduce the various models and products at a high level, which will set the stage for deeper dives later in this chapter.

Overall, the models and products are categorized by modality, such as text, code, image, and video. Let’s begin our journey with a discussion of Google’s various generative AI models.

Google’s generative AI models

Google has created many generative AI models over the past few years, with a dramatic acceleration of new models and model versions launched in the past year. This section discusses the Google first-party foundation models that are currently available on Google Cloud in early 2024, starting with the quite famous “Gemini.”