🎬 Movie Review Sentiment Analyzer

📝 Overview

The Movie Review Sentiment Analyzer is a machine learning-powered application that classifies movie reviews as Positive, Negative, or Neutral based on sentiment analysis. Using a trained Recurrent Neural Network (RNN), the app predicts the sentiment of user-inputted text and provides a confidence score.

✨ Features

• 📝 Text-based Sentiment Analysis
• 📊 Confidence Score for Sentiment Prediction
• 🎭 Emoji-based Sentiment Representation
• 🎨 Modern, User-Friendly UI with Streamlit
• 📉 Visual Progress Bar for Sentiment Strength

🛠 Technology Stack

• Python
• Streamlit
• TensorFlow/Keras
• NumPy & Pandas
• RNN

🚀 Getting Started

Prerequisites

• Python 3.8+
• TensorFlow installed
• Pretrained model (SimpleRnn_imdb.h5)
• Tokenizer file (tokenizer.pkl)

Installation

1. Clone the repository

git clone https://github.com/taskmaster-1/sentiment-analyzer.git
cd sentiment-analyzer

2. Create a virtual environment

python -m venv venv
source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install dependencies

pip install -r requirements.txt

Running the App

streamlit run app.py

📦 Requirements File

Create a requirements.txt with:

streamlit
tensorflow
numpy
pandas
pickle-mixin

🤝 Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

🔒 Security

• Never commit your model files (SimpleRnn_imdb.h5) or tokenizer files (tokenizer.pkl) to public repositories
• Use .gitignore to exclude sensitive files

📊 How It Works

1. Enter a movie review in the text box
2. Click the "Analyze Sentiment" button
3. The model predicts the sentiment (Positive, Negative, or Neutral)
4. The confidence score is displayed
5. A visual progress bar shows sentiment strength

📈 Future Roadmap

• Improve model accuracy with advanced NLP techniques
• Deploy as a web app using Streamlit Sharing or Render
• Support for multiple languages
• Live API for sentiment prediction

🏷️ Versioning

Current Version: 1.0.0

📄 License

Distributed under the MIT License. See LICENSE for more information.

🌐 Deployed Application

🔗 Live

• Render: [https://sentiment-analyzer-rncf.onrender.com]

📞 Contact

Gmail - vivekyad5223@gmail.com

Project Link: https://github.com/taskmaster-1/sentiment-analyzer

🙏 Acknowledgements

• Streamlit
• TensorFlow
• IMDB Dataset
• Python