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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

Estimating the costs for a proof-of-concept solution, including all services

To build relatively accurate costing models, Ocean Smart needed certain estimates to be made based on logic and some guesswork. When you're building your costing models, be mindful that it is very difficult to get exact costs initially. As Ocean Smart was able to bring the solution that was developed into a production state, they started to see how long it took to move data, how much data was being stored to maintain the model, how much compute was required, and how long it would take to execute model training and retraining. In turn, they began to build a basis to add more compute that was required to meet internal SLAs for processing time. The remainder of this section will go through the decisions they needed to make when it came to building an estimate for a Form Recognizer proof of concept solution in Azure. The prices and tiers of each of the components are built in the East US 2 region of Azure...

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