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Practical Guide to Azure Cognitive Services

Practical Guide to Azure Cognitive Services

By : Chris Seferlis , Christopher Nellis, Andy Roberts
4.9 (12)
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Practical Guide to Azure Cognitive Services

Practical Guide to Azure Cognitive Services

4.9 (12)
By: Chris Seferlis , Christopher Nellis, Andy Roberts

Overview of this book

Azure Cognitive Services and OpenAI are a set of pre-built artificial intelligence (AI) solution APIs that can be leveraged from existing applications, allowing customers to take advantage of Microsoft’s award-winning Vision, Speech, Text, Decision, and GPT-4 AI capabilities. With Practical Guide to Azure Cognitive Services, you’ll work through industry-specific examples of implementations to get a head-start in your production journey. You’ll begin with an overview of the categorization of Azure Cognitive Services and the benefits of embracing AI solutions for practical business applications. After that, you’ll explore the benefits of using Azure Cognitive Services to optimize efficiency and improve predictive capabilities. Then, you’ll learn how to leverage Vision capabilities for quality control, Form Recognizer to streamline supply chain nuances, language understanding to improve customer service, and Cognitive Search for next-generation knowledge-mining solutions. By the end of this book, you’ll be able to implement various Cognitive Services solutions that will help you enhance efficiency, reduce costs, and improve the customer experience at your organization. You’ll also be well equipped to automate mundane tasks by reaping the full potential of OpenAI.
Table of Contents (22 chapters)
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1
Part 1: Ocean Smart – an AI Success Story
5
Part 2: Deploying Next-Generation Knowledge Mining Solutions with Azure Cognitive Search
10
Part 3: Other Cognitive Services That Will Help Your Company Optimize Operations

Configuring Content, Actions, and Context to make recommendations

So far in the chapter, we have given you a pretty good idea of what the Personalizer service does for its audience, and we looked at what happens in the background with the machine learning algorithms and libraries that were used to develop the service. Now, we’re going to start to dig into the service itself to look at how it is configured, and what the details that go into the environment variables we’ve mentioned a few times are by looking at Features. Note the capital “F” in that last sentence for Features. Yes, that was intentional, because when we talk about Features, we are talking about an actual concept in the Personalizer service, not just the features of the service. Get it? Sometimes, the naming decisions for these things make me laugh.

When we discuss Features, we refer to a unit or grouping of Actions or Context. Features provides all the information needed to help improve...

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