Walk through the process of setting up the project to work with the Text Analytics API.
- [Instructor] Let's start by talking about the text analytics API. And I know you're raring to get into the text analytics API, but first let us set up our project where we will write the necessary code. What I'd like you to do is go into exercise files, go into the fourth folder, the ending code for chapter one. Here, pick up the baseproject.zip file and unzip that in a folder. So I have chosen to unzip that in a folder called C Developer, and I went ahead and renamed it to textanalytics.
Here, you should see a file folder structure that looks like this. Open your Terminal and visit the textanalytics folder and here go ahead and run npm install. As you're well aware, the process of npm install will look at your package.json and download all the dependencies and dev dependencies for your project. Once npm install finishes, go ahead and open this in Visual Studio Code and verify that you see a node modules folder present.
This node modules folder is what contains all the npm packages that we had specified in the package.json file. For your convenience, I have put the text analytics project, this project you're looking at, in chapter two, folder one, in the start folder. And this'll be my starting point for this chapter.
- 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
Skill Level Intermediate
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1. The Basics
2. Text Analytics API
3. Bing Spell Check API
4. Translator Text API
6. LUIS Authoring APIs
Next steps1m 7s
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