You're reading from The Definitive Guide to Google Vertex AI Accelerate your machine learning journey with Google Cloud Vertex AI and MLOps best practices

Product type Paperback

Published in Dec 2023

Publisher Packt

ISBN-13 9781801815260

Length 422 pages

Edition 1st Edition

Tools

MLOps

Concepts

Data Science

Authors (2):

Kartik Chaudhary

Jasmeet Bhatia

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Table of Contents (24) Chapters

Preface

1. Part 1:The Importance of MLOps in a Real-World ML Deployment

2. Chapter 1: Machine Learning Project Life Cycle and Challenges FREE CHAPTER

3. Chapter 2: What Is MLOps, and Why Is It So Important for Every ML Team?

4. Part 2: Machine Learning Tools for Custom Models on Google Cloud

5. Chapter 3: It’s All About Data – Options to Store and Transform ML Datasets

6. Chapter 4: Vertex AI Workbench – a One-Stop Tool for AI/ML Development Needs

7. Chapter 5: No-Code Options for Building ML Models

8. Chapter 6: Low-Code Options for Building ML Models

9. Chapter 7: Training Fully Custom ML Models with Vertex AI

10. Chapter 8: ML Model Explainability

11. Chapter 9: Model Optimizations – Hyperparameter Tuning and NAS

12. Chapter 10: Vertex AI Deployment and Automation Tools – Orchestration through Managed Kubeflow Pipelines

13. Chapter 11: MLOps Governance with Vertex AI

14. Part 3: Prebuilt/Turnkey ML Solutions Available in GCP

15. Chapter 12: Vertex AI – Generative AI Tools

16. Chapter 13: Document AI – An End-to-End Solution for Processing Documents

17. Chapter 14: ML APIs for Vision, NLP, and Speech

18. Part 4: Building Real-World ML Solutions with Google Cloud

19. Chapter 15: Recommender Systems – Predict What Movies a User Would Like to Watch

20. Chapter 16: Vision-Based Defect Detection System – Machines Can See Now!

21. Chapter 17: Natural Language Models – Detecting Fake News Articles!

22. Index

Why subscribe?

23. Other Books You May Enjoy

To get the most out of this book

You will need to have a basic understanding of machine learning and deep learning techniques. You also should have beginner-level experience with the Python programming language.

Software/hardware for the coding exercises	Operating system requirements
Python 3.8 or later	Windows, macOS, or Linux
Google Cloud SDK	Windows, macOS, or Linux
A Google Cloud Platform account	N/A

To ensure that you are using the correct Python library versions while executing the code samples, you can check out the GitHub repository of this book, where the code example notebooks also contain the version information.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

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Table of Contents (24) Chapters

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