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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

Vertex AI – Workbench

Vertex AI Workbench is a single development environment for the entire data science workflow. You can use Vertex AI Workbench’s notebook-based environment to query and explore data, develop and train a model, and run your code as part of a pipeline. Vertex AI workbench offers the following features:

  • Managed notebooks are Google-managed environments with integrations and features that help you set up and work in an end-to-end notebook-based production environment.
  • User-managed notebooks are deep learning VM image instances that are heavily customizable and are therefore ideal for users who need a lot of control over their environment.

To launch Vertex AI Workbench, navigate to the Vertex AI console and click on Workbench:

If you are using Vertex AI Workbench for the first time, you will need to enable Notebook API, which you will be prompted for after you click on Workbench. Click on ENABLE:

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