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Google Cloud Digital Leader Certification Guide

You're reading from   Google Cloud Digital Leader Certification Guide A comprehensive study guide to Google Cloud concepts and technologies

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781805129615
Length 210 pages
Edition 1st Edition
Languages
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Author (1):
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Bruno Beraldo Rodrigues Bruno Beraldo Rodrigues
Author Profile Icon Bruno Beraldo Rodrigues
Bruno Beraldo Rodrigues
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Table of Contents (21) Chapters Close

Preface 1. Part 1:Introduction to Digital Transformation with Google Cloud
2. Chapter 1: Cloud Computing Fundamentals – An Introduction to Digital Transformation FREE CHAPTER 3. Chapter 2: The Shift to Public Cloud 4. Chapter 3: Understanding the Different Cloud Computing Models 5. Part 2:Innovating with Data and Google Cloud
6. Chapter 4: The Role of Data in Digital Transformation 7. Chapter 5: Google Cloud Solutions for Data Management 8. Chapter 6: Machine Learning and Artificial Intelligence on Google Cloud 9. Part 3:Infrastructure and Platform Modernization
10. Chapter 7: Modernizing IT Infrastructure with Google Cloud 11. Chapter 8: Modernizing Applications with Google Cloud 12. Chapter 9: The Value of APIs 13. Part 4:Understanding Google Cloud Security and Operations
14. Chapter 10: Google Cloud’s Approach to Security 15. Chapter 11: IT Operations in the Cloud 16. Chapter 12: Resource Monitoring and Application Performance Management on Google Cloud 17. Part 5:Practice Exam Questions
18. Chapter 13: Sample Questions: Exam Preparation 19. Index 20. Other Books You May Enjoy

AI overview and Google’s contribution

Google has made meaningful contributions in several areas of the ML and AI space. At a high level, Google has been doing research and development in the ML space for a long time, where they’ve developed frameworks such as TensorFlow, which makes it easier to train ML models. Google also has an extensive library of models that they developed themselves, which can be applied across a variety of data and use cases. One of the most impactful projects in the natural language processing space was the development of the Transformer architecture, the foundation upon which the generative AI revolution was built. What’s interesting about the Transformer architecture is that it is based on the self-attention mechanism, where the model can learn the relationship between words in a sequence without relying on the order of the words. We’ll dive deeper into generative AI models and applications later in this chapter, but it’...

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