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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