Welcome to the final project for this course! In this project, you will demonstrate your knowledge and skills in app creation and web deployment. The project involves creating an emotion detection application using the Watson AI libraries and deploying it as a web application with Flask. You will also be required to perform various tasks and submit your results with specific nomenclature.
Emotion detection goes beyond sentiment analysis by extracting more nuanced emotions such as joy, sadness, anger, and more from text statements. This capability is essential for AI-based recommendation systems, chatbots, and various other applications. In this project, we will harness the power of Watson AI to create an emotion detection application.
To successfully complete this project, you need to perform the following tasks:
Begin by cloning the project repository to your local environment. This step will provide you with the necessary code and resources to commence your work. The original project link is: Original Project Repository. However, I have cloned it on my local machine and pushed it to a new repository for the purpose of using it in the Cloud IDE. The link to my repository is: My Repository.
Utilize the Watson NLP library to develop an emotion detection application. This application will analyze text input and identify the underlying emotions.
Ensure that the output of your emotion detection application is well-formatted and user-friendly. Users should be able to understand the identified emotions.
Package your application for ease of deployment. Provide clear and concise instructions for deploying it.
Thoroughly test your application to ensure it functions as expected. Create unit tests to validate its behavior.
Take your emotion detection application and deploy it as a web application using the Flask framework. This step involves making your application accessible over the web.
Implement robust error handling to ensure that your application gracefully handles unexpected situations.
Perform static code analysis to review your code for potential issues, code quality, and adherence to best practices.
By completing these tasks, you will have created a functional emotion detection web application that can be accessed by users on the internet.