Welcome to the Emotion Detection Web Application project! 🌟 In this journey, we'll build an AI-based web app that analyzes customer feedback using Watson NLP to extract emotions expressed in text. 🤖💬
| Technology | Purpose |
|---|---|
| Python | Primary programming language. |
| Watson NLP Library | Empowers emotion detection and analysis. |
| Flask | Web framework for building the application. |
| Unit Testing | Ensures correctness with comprehensive tests. |
| Git | Version control for efficient collaboration. |
| Static Code Analysis | Improves code quality with insightful analysis. |
Clone the project repository to your local machine.
Develop the application using Watson NLP to analyze and decipher emotions from customer feedback.
Present the emotion analysis results in a clear and visually appealing format.
Prepare the application for deployment, specifying dependencies and organizing the project structure.
Ensure the application's correctness by creating and running comprehensive unit tests.
Utilize Flask to transform the application into a user-friendly web service, with routes for input and result display.
Implement graceful error handling for situations like API call failures or invalid inputs.
Use static code analysis tools to maintain code quality, following best practices and standards.
Let's embark on this exciting journey of creating a seamless Emotion Detection Web Application! 💻🌈