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Practical Guide to Azure Cognitive Services

You're reading from  Practical Guide to Azure Cognitive Services

Product type Book
Published in May 2023
Publisher Packt
ISBN-13 9781801812917
Pages 454 pages
Edition 1st Edition
Languages
Authors (3):
Chris Seferlis Chris Seferlis
Profile icon Chris Seferlis
Christopher Nellis Christopher Nellis
Profile icon Christopher Nellis
Andy Roberts Andy Roberts
Profile icon Andy Roberts
View More author details

Table of Contents (22) Chapters

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

Defining and detecting anomalies in your organization

Beyond giving examples of how the services can be deployed, this book intends to provide some insight on how to apply AI, hopefully helping to streamline operations and other related benefits. When you start to analyze activities where you might be able to use AI, it helps to look at where unexpected events can occur and how you can better predict the potential for failure. Even if the prediction is especially challenging, there is likely an opportunity to monitor equipment and other capital resources for unexpected events and develop predictability over time.

An area of interest where Ocean Smart could expand is to use the Multivariate detector to look at the overall freezer health, including some of the various elements of a freezer. Then taking that example, similar logic could be applied across locations for all freezers and chillers. This could potentially save significant electricity overhead costs and extend the life of...

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