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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

ML services

One of the strongest points of Google is its long-term experience with ML. GCP offers several services around ML. You can choose between a pre-trained model or training the model yourself. The various services included under ML are as follows:

  • Cloud ML Engine: ML Engine is a managed service that allows you to train and host your ML models in GCP. It leverages the TensorFlow application for the training process. The underlying infrastructure is managed by Google, while users can choose from different hardware options. The trained model can be accessed through APIs to perform predictions.
  • Pretrained APIs: ML APIs are services that allow you to leverage several pre-trained models, enabling you to analyze a video. Currently, the following APIs are available:
    • Google Cloud Video Intelligence
    • Google Cloud Speech
    • Google Cloud Vision
    • Google Cloud Natural Language
    • Google Cloud...
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