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Sentiment Analysis on Tweets for Brand Monitoring

A web application that analyzes the sentiment of tweets to help with brand monitoring. The application uses a pre-trained machine learning model to classify tweets as positive, negative, or neutral, and provides an accuracy score for each prediction.

Features
Clean, modern UI with dark purple, black, and yellow color scheme
Simple interface for entering tweets
Real-time sentiment analysis
Displays sentiment classification (Positive, Negative, or Neutral)
Shows prediction accuracy percentage
Responsive design for desktop and mobile
Project Structure
The project consists of two main components:

Frontend: A web application built with Typescript and Tailwind CSS

Python API: A Flask API that serves the ML model for sentiment prediction


visit : https://sentiment-analysis-app-xi.vercel.app/

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