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🎭 Emotion Detection App

Streamlit App
Python
Scikit-Learn

Live app: πŸ”— Open Live App (Streamlit)

πŸ“– Overview

The Emotion Detection App is an NLP-powered web application that predicts the underlying emotion in user input text.
It is built using TF-IDF + Logistic Regression, achieving 85% accuracy 🎯.

✨ Features :

🎨 Clean & modern Streamlit UI πŸ˜ƒ Six supported emotions: Joy, Sadness, Anger, Fear, Surprise, Love πŸ€– Emoji-based prediction for better visualization ☁️ Deployed on Streamlit Community Cloud

βš™οΈ Installation & Usage

Clone the repository

git clone https://github.com/YOUR_USERNAME/EmotionDetect.git cd EmotionDetect

Install dependencies

pip install -r requirements.txt

Run the app locally

streamlit run app.py

🧠 How It Works

  1. Input text is preprocessed and converted into vectors using TF-IDF
  2. Logistic Regression classifies the text into one of six emotions
  3. The app displays the predicted emotion with an emoji

πŸš€ Deployment This project is deployed on Streamlit Community Cloud. πŸ‘‰ https://emotiondetect-2ysbluimrqdsuvqh87qbz4.streamlit.app/

πŸ“Œ Future Improvements

  • Add more emotions & larger datasets
  • Deploy with Docker / Hugging Face Spaces
  • Use Transformers (BERT, RoBERTa) for higher accuracy

πŸ‘¨β€πŸ’» Author Made by Krish (https://github.com/Krish00711)

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🎭 NLP-powered Emotion Detection App using TF-IDF + Logistic Regression | Streamlit Deployment

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