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Practical Guide to Azure Cognitive Services

You're reading from   Practical Guide to Azure Cognitive Services Leverage the power of Azure OpenAI to optimize operations, reduce costs, and deliver cutting-edge AI solutions

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Product type Paperback
Published in May 2023
Publisher Packt
ISBN-13 9781801812917
Length 454 pages
Edition 1st Edition
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Authors (3):
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Andy Roberts Andy Roberts
Author Profile Icon Andy Roberts
Andy Roberts
Chris Seferlis Chris Seferlis
Author Profile Icon Chris Seferlis
Chris Seferlis
Christopher Nellis Christopher Nellis
Author Profile Icon Christopher Nellis
Christopher Nellis
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Toc

Table of Contents (22) Chapters Close

Preface 1. Part 1: Ocean Smart – an AI Success Story
2. Chapter 1: How Azure AI Changed Ocean Smart FREE CHAPTER 3. Chapter 2: Why Azure Cognitive Services? 4. Chapter 3: Architectural and Cost Optimization Considerations 5. Part 2: Deploying Next-Generation Knowledge Mining Solutions with Azure Cognitive Search
6. Chapter 4: Deriving Value from Knowledge Mining Solutions in Azure 7. Chapter 5: Azure Cognitive Search Overview and Implementation 8. Chapter 6: Exploring Further Azure Cognitive Services for Successful KM Solutions 9. Chapter 7: Pulling It All Together for a Complete KM Solution 10. Part 3: Other Cognitive Services That Will Help Your Company Optimize Operations
11. Chapter 8: Decluttering Paperwork with Form Recognizer 12. Chapter 9: Identifying Problems with Anomaly Detector 13. Chapter 10: Streamlining the Quality Control Process with Custom Vision 14. Chapter 11: Deploying a Content Moderator 15. Chapter 12: Using Personalizer to Cater to Your Audience 16. Chapter 13: Improving Customer Experience with Speech to Text 17. Chapter 14: Using Language Services in Chat Bots and Beyond 18. Chapter 15: Surveying Our Progress 19. Chapter 16: Appendix – Azure OpenAI Overview 20. Index 21. Other Books You May Enjoy

Building the complete Custom Vision solution

In this chapter, we use Cognitive Services to train a predictive model and deploy the model to a web endpoint to classify new images as they arrive. The following diagram provides an overview of how the tail images are processed and tested against our model to determine whether they are good or bad, as well as how we can frequently update the model to handle new examples:

Figure 10.14 – Process flow of tail image classification testing against machine learning model

Figure 10.14 – Process flow of tail image classification testing against machine learning model

To support this process, we create the following:

  • The cognitive services and custom vision workspace.
  • A storage account where new images and results will be stored and a storage table will be used to communicate results to the frontend web application.
  • A function app that contains functions to do the following:
    1. Classify new images as they arrive. It is important to note that we were able to utilize the model trained for the...
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