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Professional Cloud Architect –  Google Cloud Certification Guide

You're reading from   Professional Cloud Architect – Google Cloud Certification Guide A handy guide to designing, developing, and managing enterprise-grade GCP cloud solutions

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Product type Paperback
Published in Oct 2019
Publisher Packt
ISBN-13 9781838555276
Length 520 pages
Edition 1st Edition
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Authors (2):
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Brian Gerrard Brian Gerrard
Author Profile Icon Brian Gerrard
Brian Gerrard
Konrad Cłapa Konrad Cłapa
Author Profile Icon Konrad Cłapa
Konrad Cłapa
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Toc

Table of Contents (26) Chapters Close

Preface 1. Section 1: Introduction to GCP FREE CHAPTER
2. GCP Cloud Architect Professional 3. Getting Started with Google Cloud Platform 4. Google Cloud Platform Core Services 5. Section 2: Managing, Designing, and Planning a Cloud Solution Architecture
6. Working with Google Compute Engine 7. Managing Kubernetes Clusters with Google Kubernetes Engine 8. Exploring Google App Engine as a Compute Option 9. Running Serverless Functions with Google Cloud Functions 10. Networking Options in GCP 11. Exploring Storage Options in GCP - Part 1 12. Exploring Storage Options in GCP - Part 2 13. Analyzing Big Data Options 14. Putting Machine Learning to Work 15. Section 3: Designing for Security and Compliance
16. Security and Compliance 17. Section 4: Managing Implementation
18. Google Cloud Management Options 19. Section 5: Ensuring Solution and Operations Reliability
20. Monitoring Your Infrastructure 21. Section 6: Exam Focus
22. Case Studies 23. Test Your Knowledge 24. Assessments 25. Other Books You May Enjoy

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
  • Cloud ML Engine
  • Pretrained...
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