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How do people feel about a product? Use AI to get the answer

Natural language processing (NLP) is an exciting machine learning application; IBM's Watson NLP library can greatly ease the development and deployment of NLP as part of your application. Amazon's 5-star rating system lacks feedback for both users and buyers. What about using NLP for helpful information? In this project, we will develop an application to classify Amazon users' emotions using Watson NLP. After conducting this project, developers will know how to build a web scraping, emotion classification embedded application.

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Guided Project

Artificial Intelligence

426 Enrolled
(60)

At a Glance

Natural language processing (NLP) is an exciting machine learning application; IBM's Watson NLP library can greatly ease the development and deployment of NLP as part of your application. Amazon's 5-star rating system lacks feedback for both users and buyers. What about using NLP for helpful information? In this project, we will develop an application to classify Amazon users' emotions using Watson NLP. After conducting this project, developers will know how to build a web scraping, emotion classification embedded application.

Introduction



Natural language processing (NLP) plays a crucial role in today's AI landscape. One such library designed for NLP tasks is Watson NLP, which offers a wide range of functions including document understanding, translation, and trust assessment. This library simplifies the development and deployment process of NLP models. You can use the Watson NLP library to enhance your application with sophisticated NL functionality to deliver better value to the users of your application.  


In the Amazon marketplace, it's common for products to receive 4-5 star ratings. However, this system is limited and fails to provide a full picture of the buyer's experience. To address this issue, NLP models can be applied to product reviews to gain deeper insights into customer feedback.


In this project, we will walk you through the process of building an application that uses Watson_NLP to classify reviews from Amazon product links. We will provide step-by-step instructions and code snippets to help you build this application. Let's get started!



A Look at the Project Ahead

In the application, we first web scrap Amazon reviews, then conduct emotion classification for the reviews
  • Web scrapping using BeautifulSoup
  • Emotion classification using Watson_nlp
  • Build a simple but  real functional application

What You'll Need

Users need to know basic python and HTML to start the project. But the knowledge requirement is in a very preliminary stage. This project is beginner-friendly. 
Remember that the IBM Skills Network Labs environment comes with many things pre-installed (e.g. Docker) to save them the hassle of setting everything up. Also note that this platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer or Safari.