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Journey to Become a Google Cloud Machine Learning Engineer

You're reading from   Journey to Become a Google Cloud Machine Learning Engineer Build the mind and hand of a Google Certified ML professional

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803233727
Length 330 pages
Edition 1st Edition
Languages
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Author (1):
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Dr. Logan Song Dr. Logan Song
Author Profile Icon Dr. Logan Song
Dr. Logan Song
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Table of Contents (23) Chapters Close

Preface 1. Part 1: Starting with GCP and Python
2. Chapter 1: Comprehending Google Cloud Services FREE CHAPTER 3. Chapter 2: Mastering Python Programming 4. Part 2: Introducing Machine Learning
5. Chapter 3: Preparing for ML Development 6. Chapter 4: Developing and Deploying ML Models 7. Chapter 5: Understanding Neural Networks and Deep Learning 8. Part 3: Mastering ML in GCP
9. Chapter 6: Learning BQ/BQML, TensorFlow, and Keras 10. Chapter 7: Exploring Google Cloud Vertex AI 11. Chapter 8: Discovering Google Cloud ML API 12. Chapter 9: Using Google Cloud ML Best Practices 13. Part 4: Accomplishing GCP ML Certification
14. Chapter 10: Achieving the GCP ML Certification 15. Part 5: Appendices
16. Index 17. Other Books You May Enjoy Appendix 1: Practicing with Basic GCP Services 1. Appendix 2: Practicing Using the Python Data Libraries 2. Appendix 3: Practicing with Scikit-Learn 3. Appendix 4: Practicing with Google Vertex AI 4. Appendix 5: Practicing with Google Cloud ML API

Exploring Google Cloud Vertex AI

In the last chapter, we discussed Google Cloud BQML, which is used to develop ML models from structured data, and Google’s TensorFlow and Keras frameworks, which provide a high-level API interface for ML model development. In this chapter, we will discuss Cloud Vertex AI, which is Google’s integrated cloud service suite for ML model development. We will examine the Vertex AI suite and all its products and services.

Google Vertex AI is an integrated set of Google Cloud products, features, and a management interface that simplifies the management of ML services. It offers users a complete platform to build, train, and deploy ML applications in Google Cloud, from end to end. Vertex AI provides a single stop for data scientists to build machine learning applications.

In this chapter, we will discuss the following Vertex AI products and services:

  • Vertex AI data labeling and datasets
  • Vertex AI Feature Store
  • Vertex AI Workbench...
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