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Professional Cloud Architect Google Cloud Certification Guide

You're reading from   Professional Cloud Architect Google Cloud Certification Guide Build a solid foundation in Google Cloud Platform to achieve the most lucrative IT certification

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Product type Paperback
Published in Dec 2021
Publisher Packt
ISBN-13 9781801812290
Length 664 pages
Edition 2nd Edition
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Authors (2):
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Konrad Cłapa Konrad Cłapa
Author Profile Icon Konrad Cłapa
Konrad Cłapa
Brian Gerrard Brian Gerrard
Author Profile Icon Brian Gerrard
Brian Gerrard
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Toc

Table of Contents (25) Chapters Close

Preface 1. Section 1: Introduction to GCP
2. Chapter 1: GCP Cloud Architect Professional FREE CHAPTER 3. Chapter 2: Getting Started with Google Cloud Platform 4. Chapter 3: Google Cloud Platform Core Services 5. Section 2: Manage, Design, and Plan a Cloud Solution Architecture
6. Chapter 4: Working with Google Compute Engine 7. Chapter 5: Exploring Google App Engine as a Compute Option 8. Chapter 6: Managing Kubernetes Clusters with Google Kubernetes Engine 9. Chapter 7: Deploying Cloud-Native Workloads with Cloud Run 10. Chapter 8: Managing Cloud-Native Workloads with Anthos 11. Chapter 9: Running Serverless Functions with Google Cloud Functions 12. Chapter 10: Networking Options in GCP 13. Chapter 11: Exploring Storage and Database Options in GCP – Part 1 14. Chapter 12: Exploring Storage and Database Options in GCP – Part 2 15. Chapter 13: Analyzing Big Data Options 16. Chapter 14: Putting Machine Learning to Work 17. Section 3: Secure, Manage and Monitor a Google Cloud Solution
18. Chapter 15: Security and Compliance 19. Chapter 16: Google Cloud Management Options 20. Chapter 17: Monitoring Your Infrastructure 21. Section 4: Exam Focus
22. Chapter 18: Case Studies 23. Chapter 19: Test Your Knowledge 24. Other Books You May Enjoy

Chapter 14: Putting Machine Learning to Work

As we have already mentioned, machine learning (ML) is one of the differentiators of the Google Cloud Platform (GCP). You should pay special attention to this chapter, as you will be learning that you don't actually need to be a data scientist to leverage ML in your applications. Google has options for both beginners and highly experienced consumers. ML can be quite an intimidating topic for many people but, hopefully, we will be able to explain the basic underlying concepts by means of easy examples. Having that understanding, we will then be able to look at the ML services that we can use in GCP. Hopefully, you are as excited about this chapter as we were when writing it.

In this chapter, we will cover the following topics:

  • An introduction to AI and ML
  • The seven steps of ML
  • Learning models
  • GCP ML options
  • TensorFlow
  • Vertex AI
  • Pretrained ML models
  • Dialogflow
  • AutoML

    Exam Tip

    Interestingly, the...

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