Beginning Azure Cognitive Services
eBook Details:
- Paperback: 328 pages
- Publisher: WOW! eBook (August 28, 2021)
- Language: English
- ISBN-10: 1484271750
- ISBN-13: 978-1484271759
eBook Description:
Beginning Azure Cognitive Services: Data-Driven Decision Making Through Artificial Intelligence
Get started with Azure Cognitive Services and its APIs that expose machine learning as a service. This book introduces the suite of Azure Cognitive Services and helps you take advantage of the proven machine learning algorithms that have been developed by experts and made available through Cognitive Services, easily integrating those algorithms into your own applications without having to develop the algorithms from scratch. The book also shows you how to use the algorithms provided by Cognitive Services to accelerate data analysis and development within your organization.
The authors begin by introducing the tools and describing the steps needed to invoke libraries to analyze structured and unstructured text, speech, and pictures, and you will learn to create interactive chatbots using the Cognitive Services libraries. Each chapter contains the information you need to implement artificial intelligence (AI) via Azure Cognitive Services in your personal and professional projects.
What You Will Learn
- Invoke the Cognitive Services APIs from a variety of languages and apps
- Understand common design architectures for AI solutions in Azure
- Decrease discrimination and bias when creating an AI-driven solution
- Execute the examples within the book and learn how to extend those examples
- Implement best practices for leveraging the Vision, Speech, and Language parts of the suite
- Test Cognitive Services APIs via the Azure portal and using the Postman API tool
- Execute AI from low-code and no-code platforms like Logic Apps and Microsoft’s Power Platform
The Beginning Azure Cognitive Services book also covers ethical considerations that are becoming increasingly of concern when using AI to drive decision making. You will be introduced to tools such as FairLearn and InterpretML that can help you detect bias and understand the results your models are generating.
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