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

Building the complete solution in Azure

Here, we will use the Anomaly Detector service to look for anomalies in refrigerator temperature readings. This example is a slice of what might exist in a real-world implementation; however, we have simplified the flow so we may concentrate on the Cognitive Service and not a full-blown IoT implementation. For our example, we will use the following diagram as our reference architecture:

Figure 9.2 – Reference architecture for the example of building an anomaly detector in an operational service

Figure 9.2 – Reference architecture for the example of building an anomaly detector in an operational service

The basic building blocks of this solution include the following:

  • An Azure function to simulate the refrigerator readings.
    • For ease of deployment and to keep things in one place, for this example, we have implemented the simulator as an Azure function. You could take the same basic code and implement it outside of Azure as well – as long as you have connectivity to the Azure Event Hub.
  • An Azure Event...