Final Project - Emotion Detector

Watson AI

Guidelines

You have been hired as a software engineer by an e-commerce company to create an AI-based web app that performs analytics on customer feedback for their signature products. To accomplish this requirement, you will create an Emotion Detection system that processes feedback provided by the customer in text format and deciphers the associated emotion expressed.
In this final project, you will be assessed on the knowledge gained on all aspects of app creation and its web deployment throughout this course. You will be required to save screenshots of your results from time to time, with specific nomenclature. These screenshots will have to be uploaded in the peer graded assignment that follows.
1. Task 1: Clone the project repository
2. Task 2: Create an emotion detection application using Watson NLP library
3. Task 3: Format the output of the application
4. Task 4: Package the application
5. Task 5: Run Unit tests on your application
6. Task 6: Deploy as web application using Flask
7. Task 7: Incorporate Error handling
8. Task 8: Run static code analysis

In this project, we use the embeddable Watson AI libraries to create an emotion detection application.
Emotion detection extends the concept of sentiment analysis by extracting the finer emotions, like joy, sadness, anger, and so on, from statements rather than the simple polarity that sentiment analysis provides. This makes emotion detection a very important branch of study and businesses use such systems widely for their AI based recommendation systems, automated chat bots, and so on.