Example: Building a Sentiment Analysis Web Application

Sentiment analysis is a natural language processing technique that identifies and extracts subjective opinions from textual data sources. It is widely used in various applications, such as social media analysis, customer feedback analysis, product analysis and much more. In this project, we will develop a sentiment analysis web application that predicts the sentiment (positive, negative, neutral) of the text entered by the user.

Project overview

The project involves an application that will have a simple interface where users can enter text. The text will be processed, and the sentiment of the text will be predicted and displayed. The heart of this application is a machine learning model trained on a large dataset of tweets labeled with sentiment. The model is built using the PyTorch machine learning library and is integrated into the web application using Flask, a popular Python web framework.

The project workflow is...