Book Image

Practical Guide to Azure Cognitive Services

By : Chris Seferlis, Christopher Nellis, Andy Roberts
Book Image

Practical Guide to Azure Cognitive Services

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)
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

Summary

This chapter covered how the Form Recognizer service was deployed for Ocean Smart with details of the challenges encountered when building the solution. This includes deploying the storage used for document loading, storing, and processing. We also deployed a database for storing the details captured from the document processing with all the required settings for ensuring a secure deployment as well. For our example, we chose to use a Docker container with associated compute requirements to deploy our Form Recognizer example, so be sure to evaluate all options for your deployment. Finally, we provided an example of how Ocean Smart built an interface for the manual upload and processing of documents using the Django framework. There are many ways the service can be used in a production environment, while this chapter provided one option for building your own solution, so evaluate your options for your own deployments.

In the next chapter, we are going to explore how anomalies...