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)
Part 1: Ocean Smart – an AI Success Story
Part 2: Deploying Next-Generation Knowledge Mining Solutions with Azure Cognitive Search
Part 3: Other Cognitive Services That Will Help Your Company Optimize Operations

Configuring and refining monitoring of data in your environment

Now that we have had a chance to look at what the Async and Sync APIs offer in the way of anomaly detection and the differences between the Univariate and Multivariate services, let’s look at how to put this detailed understanding of the APIs into practice.

In the example we built for later in this chapter, you will find that we wanted to provide a simple example of how to send data from our freezer into Azure to leverage the service using an Event Hub. If we did not have the option to send the data to the cloud because of security reasons, or unavailability of internet connectivity, we could have used the Univariate service in a Docker container deployed to an IoT device. This could present other challenges for how to report on the anomalies and trend analysis but could be handled with other Microsoft products that can still be deployed on-premises, such as Power BI Report Server. Currently, only the Univariate...