Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803233727
Length 330 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Dr. Logan Song Dr. Logan Song
Author Profile Icon Dr. Logan Song
Dr. Logan Song
Arrow right icon
View More author details
Toc

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 – predictions (Vertex AI Endpoint)

In this section, we are going to deploy our model via Vertex AI Endpoint. There are two ways to deploy a model:

  • From Models
  • From Endpoints

Let’s look at these options in detail.

Deploying the model via Models

Go to the Models section from the left menu, select the model you want to deploy, and select the version you want to deploy (remember, we have only one version since we have built/trained a brand-new model). Then, at the top of the page, click on DEPLOY & TEST:

After clicking on DEPLOY & TEST, you will be taken to the next page. Here, click on the blue DEPLOY TO ENDPOINT button:

Deploying the model via Endpoints

Go to the Endpoints section from the left menu. By doing so, you will be navigated to a pop-up page where you need to define your endpoint:

On the next page, you need to specify which model you want...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime