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Final Project: Emotion Detection Application

This is the final project for the Developing AI Applications with Python and Flask course on Coursera. This project aims to demonstrate knowledge and skills in application creation and web deployment.

Project Overview

The project involves developing an emotion detection application using the Watson AI libraries and deploying it as a web application with Flask. The application will analyze text input to identify underlying emotions, providing a user-friendly output format.

Project Tasks

To successfully complete this project, there are 8 tasks that need to be performed:

Task 1: Clone the Project Repository

Clone the original project repository to your local environment for the necessary code and resources.

Task 2: Create an Emotion Detection Application

Utilize the Watson NLP library to develop an application that analyzes text input and identifies the emotions present.

Task 3: Format the Output

Ensure the output of the emotion detection application is well-formatted and user-friendly, allowing users to understand the identified emotions.

Task 4: Package the Application

Prepare the application for deployment with clear and concise instructions.

Task 5: Run Unit Tests

Thoroughly test the application to ensure it functions as expected. Create unit tests to validate its behavior.

Task 6: Deploy as a Web Application Using Flask

Deploy the emotion detection application as a web application using the Flask framework, making it accessible over the internet.

Task 7: Incorporate Error Handling

Implement robust error handling to manage unexpected situations gracefully.

Task 8: Run Static Code Analysis

Perform static code analysis to review the code for potential issues, ensuring adherence to best practices and code quality.

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  • Python 71.4%
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  • JavaScript 7.4%