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Architecting Google Cloud Solutions

You're reading from   Architecting Google Cloud Solutions Learn to design robust and future-proof solutions with Google Cloud technologies

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Product type Paperback
Published in Apr 2021
Publisher Packt
ISBN-13 9781800563308
Length 472 pages
Edition 1st Edition
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Author (1):
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Victor Dantas Victor Dantas
Author Profile Icon Victor Dantas
Victor Dantas
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Introduction to Google Cloud
2. Chapter 1: An Introduction to Google Cloud for Architects FREE CHAPTER 3. Chapter 2: Mastering the Basics of Google Cloud 4. Section 2: Designing Great Solutions in Google Cloud
5. Chapter 3: Designing the Network 6. Chapter 4: Architecting Compute Infrastructure 7. Chapter 5: Architecting Storage and Data Infrastructure 8. Chapter 6: Configuring Services for Observability 9. Chapter 7: Designing for Security and Compliance 10. Section 3: Designing for the Modern Enterprise
11. Chapter 8: Approaching Big Data and Data Pipelines 12. Chapter 9: Jumping on the DevOps Bandwagon with Site Reliability Engineering (SRE) 13. Chapter 10: Re-Architecting with Microservices 14. Chapter 11: Applying Machine Learning and Artificial Intelligence 15. Chapter 12: Achieving Operational Excellence 16. Other Books You May Enjoy

Leveraging pretrained models on GCP with ML APIs

Google's pretrained models are offered as a suite of ready-to-consume APIs. These are described in the following table:

These services can often be combined to deliver an ML-powered solution. For example, you could combine the Speech-to-Text and Natural Language APIs to extract meaning from audio conversations. Or you could combine the Vision and Translation APIs to detect and translate text content within images.

The main appeal behind these services is that they're easy to consume. For example, the Text-to-Speech API has a demo available at https://cloud.google.com/text-to-speech. You can experiment using different texts and voice parameters and listen to the result. By clicking on Show JSON, you can see the underlying (and relatively uncomplicated) API call, as shown in the following screenshot:

Figure 11.3 – Text-to-Speech API usage example

As another example...

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