Book Image

Learning Microsoft Cognitive Services - Second Edition

By : Leif Larsen
Book Image

Learning Microsoft Cognitive Services - Second Edition

By: Leif Larsen

Overview of this book

Microsoft has revamped its Project Oxford to launch the all new Cognitive Services platform-a set of 30 APIs to add speech, vision, language, and knowledge capabilities to apps. This book will introduce you to 24 of the APIs released as part of Cognitive Services platform and show you how to leverage their capabilities. More importantly, you'll see how the power of these APIs can be combined to build real-world apps that have cognitive capabilities. The book is split into three sections: computer vision, speech recognition and language processing, and knowledge and search. You will be taken through the vision APIs at first as this is very visual, and not too complex. The next part revolves around speech and language, which are somewhat connected. The last part is about adding real-world intelligence to apps by connecting them to Knowledge and Search APIs. By the end of this book, you will be in a position to understand what Microsoft Cognitive Service can offer and how to use the different APIs.
Table of Contents (19 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Chapter 7. Extending Knowledge Based on Context

"By leveraging Azure Machine Learning and the Recommendations API, we have launched a new Personalized Commerce Experience for retailers that grows shopper conversion and engagement on any channel."

- Frank Kouretas, Chief Product Officer at Orckestra

With the previous chapter, we covered the remaining Language APIs. In this chapter, we will look into the first two Knowledge APIs: the Entity Linking API and the Recommendations API. We will start by learning how to link entities in text. Using the Entity Linking API, we can identify different entities in text, based on the context. Moving on, we will look into the Recommendations API. This is well-suited for e-commerce applications, where you can recommend different items based on different criteria.

With this chapter completed, we will have covered the following topics:

  • Recognizing and identifying separate entities in text, based on context
  • Recommending items based on items frequently bought together...