🎭 RNN Sentiment Analysis

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📖 Overview

This project implements a Simple Recurrent Neural Network (RNN) model for sentiment analysis on the IMDB movie review dataset.
The model classifies reviews as positive or negative based on textual input.

It also includes a Streamlit web app that allows users to input custom reviews and receive predictions in real time.

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📑 Table of Contents

• Overview
• Quickstart
• Features
• Project Structure
• Roadmap
• Contribution
• License
• Acknowledgements

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⚡ Quickstart

🔹 Clone Repository

git clone https://github.com/anjaliy11/RNN_sentimental_analysis.git
cd RNN_sentimental_analysis

🔹 Install Dependencies

pip install -r requirements.txt

🔹 Train the Model

jupyter notebook
simple_rnn.ipynb
prediction.ipynb

🔹 Run the Streamlit App

streamlit run main.py

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✨ Features

✅ Train an RNN on the IMDB dataset
✅ Sentiment classification (Positive / Negative)
✅ Interactive Streamlit app for real-time predictions
✅ Preprocessing of text using word embeddings and padding
✅ High accuracy model with user-friendly interface

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📂 Project Structure

RNN_sentimental_analysis/
│── main.py                 # Streamlit app for predictions
│── simple_rnn.ipynb                # Training script for RNN model
│── simple_rnn_imdb.keras   # Saved model file
│── requirements.txt        # Required dependencies
│── README.md               # Project documentation

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🗺 Roadmap

• Improve model generalization with LSTM/GRU
• Add more datasets for robust sentiment classification
• Enhance UI with advanced visualization
• Deploy app on cloud (Heroku/Streamlit Cloud)

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🤝 Contribution

Contributions are welcome!

1. Fork the repo
2. Create a new branch (feature-xyz)
3. Commit your changes
4. Open a Pull Request

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📜 License

This project is licensed under the MIT License.

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🙌 Acknowledgements

• TensorFlow
• Keras
• IMDB Dataset
• Streamlit

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