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

Reviewing a brief history of document collection solutions

The term knowledge mining is much newer than the concept, with a 21st-century enhancement that includes the cloud and AI. In fact, organizations around the world have sought after a centralized management system of their documents and other assets containing company-specific information for decades now. When we consider that document management systems (DMSees) have been around for decades, due to a proliferation of documents and data, it is no surprise that the opportunity has surfaced to align with AI for enhancements. These systems were developed to have a central repository of documents for archival and reference. DMSees align context with the documents themselves by providing tags and hierarchical structure for simpler retrieval and searching. tagging and describing documents is manual in process, as each document needs to be described and tagged individually. As the volume and variety of documents increase dramatically...