Microsoft Cognitive Services for Developers: 3 Language

Course details

The Microsoft Cognitive Services APIs allow developers to leverage the power of artificial intelligence to create apps that can more effectively understand and interpret the needs of users. In this course, learn how to work with Microsoft Cognitive Services for language. Instructor Sahil Malik explains how to work with the Bing Spell Check API, the Text Analytics API—which you can use to detect language, key phrases, and sentiment—and the Translator Text API. He wraps up the course by taking a deep dive into the exciting Language Understanding (LUIS) service, which allows apps to accept a user's input in natural language.

Learning objectives
Text Analytics API
Detecting language using text analytics
Detecting key phrases and sentiment
Bing Spell Check API
Translator Text API
Writing code for translating between languages
Performing text-to-speech
Language Understanding (LUIS)
Writing code to create a LUIS app

Concepts

0. Introduction

01 - Welcome
02 - What you should know
03 - Using the exercise files

1. The Basics

04 - Introduction
05 - Set up a Node.js project
06 - Add TypeScript debugging support
07 - Add helper code and debugging

2. Text Analytics API

08 - Set up your Node.js project
09 - Register Text Analytics API in Azure
10 - Detect language using text analytics
11 - Detect key phrases
12 - Detect sentiment

3. Bing Spell Check API

13 - Register in Azure and set up the Node.js project
14 - Bing spell check using GET requests
15 - Bing spell check using POST requests

4. Translator Text API

16 - Set up the project
17 - Set up the Translator Text API in Azure and update the project
18 - Write code for getting supported languages
19 - Get supported languages running and refactor the code
20 - Get supported languages using an access token
21 - Get supported languages using access token
22 - Get language names
23 - Write code for translating between languages
24 - Translations between multiple languages
25 - Breaking apart longer sentences
26 - Translate lots of content using TranslateArray
27 - Get languages for Speak
28 - Performing text-to-speech

5. LUIS

29 - LUIS basics
30 - Create a new LUIS app
31 - Add keys from Azure into LUIS applications
32 - Adding a prebuilt model, train, and publish the app
33 - Test the application in the LUIS portal
34 - Call the LUIS app from code
35 - Delete the LUIS app

6. LUIS Authoring APIs

36 - Set up the project with the correct keys and configuration
37 - Define the application domain
38 - Creating business objects
39 - Write code for parsing the model
40 - Create the structure of the main program
41 - Write code to create a LUIS app
42 - Write code to add intents into the application
43 - Write code to add entities in the application
44 - Write code to add utterances
45 - Run the application and get the model created and running
46 - AI in action with fuzzy commands

Conclusion

47 - Next steps