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  5. Analyzing Text by Using the Azure Text Analytics Service

Summary

Contents

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Text Analytics with Azure
1
Introduction
PREVIEW1m 52s
3
Demo
5m 34s
4
Summary
1m 23s
Start course
Overview
Difficulty
Intermediate
Duration
15m
Students
36
Ratings
5/5
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Description

This course covers how to use the text analytics features in Azure to detect language, as well as how to retrieve and process key phrases, entities, and sentiment from a text. We'll provide you with a practical understanding of these features thanks to a real-life demonstration on the Azure platform.

Learning Objectives

  • Understand what text analytics is and its use cases
  • Create the Azure resources for carrying out text analytics
  • Use Azure to retrieve and process phrases, entities, and sentiment from a text

Intended Audience

This course is meant for developers or architects who would like to know more about how to use the text analytics capabilities of Azure Cognitive Service for Language to understand and process text content.

Prerequisites

To get the most out of this course, you should have basic Azure experience, knowledge of Azure Cognitive Services, and some developer experience, including familiarity with terms such as REST API and SDK.

Transcript

You’ve made it, that’s the end of the course! Congratulations!

Let’s review a few takeaways from this course.

Text Analytics allows you to extract meaningful insights from text-based data, in an automated and scalable way.

In its earlier versions, Text Analytics was a service on its own. However, Microsoft recently consolidated all language-related services into Azure Cognitive Service for Language, which also comprises QnA Maker and LUIS.

Although Microsoft is currently expanding these language services – with several new services in preview – the main capabilities related to Text Analytics are:

  • Language Detection, which determines the language the text is written in;
  • Key Phrase Extraction, which obtains the most meaningful words in a sentence;
  • Sentiment Analysis, which defines how positive (or negative) a phrase is;
  • Named Entity Recognition, which identifies pre-determined classes such as names and organizations;
  • And Entity Linking, which cross-reference entities with Wikipedia articles for better context about a detected class.

This concludes our course “Analyzing Text by Using the Azure Text Analytics Service”. I’m truly honored that you have gotten this far in it, and I recommend you continue your journey to learn more about this exciting technology! Thanks for watching!

About the Author
Avatar
Emilio Melo
Instructor
Students
1284
Courses
4

Emilio Melo has been involved in IT projects in over 15 countries, with roles ranging across support, consultancy, teaching, project and department management, and sales—mostly focused on Microsoft software. After 15 years of on-premises experience in infrastructure, data, and collaboration, he became fascinated by Cloud technologies and the incredible transformation potential it brings. His passion outside work is to travel and discover the wonderful things this world has to offer.