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+# IMDB Sentiment Analysis Project
+
+## Overview
+
+This project implements a sentiment analysis system for IMDB movie reviews using various machine learning and deep learning techniques. It includes a React frontend for user interaction and a Flask backend for processing and analyzing the reviews.
+
+## Features
+
+- Sentiment analysis of IMDB movie reviews
+- Multiple machine learning models:
+  - Naive Bayes (Gaussian NB)
+  - Random Forest
+  - Logistic Regression
+  - LSTM
+  - Transformer
+- Interactive web interface for real-time analysis
+- Visualization of model accuracies and dataset distribution
+- User feedback system for continuous improvement
+
+## Technologies Used
+
+- Frontend: React, Recharts, Lucide React
+- Backend: Flask, NLTK, SpaCy, scikit-learn, TensorFlow/Keras
+- Data Processing: Pandas, NumPy
+- Machine Learning: scikit-learn, TensorFlow, Keras
+- Natural Language Processing: NLTK, SpaCy
+
+## Setup Instructions
+
+### Prerequisites
+
+- Node.js and npm
+- Python 3.7+
+- Git
+
+### Frontend Setup
+
+1. Clone the repository:
+   ```
+   git clone https://github.com/saquib34/zensibleInterview.git
+   ```
+2. Navigate to the project directory:
+   ```
+   cd zensibleInterview
+   ```
+3. Install dependencies:
+   ```
+   npm install
+   ```
+4. Start the development server:
+   ```
+   npm start
+   ```
+
+### Backend Setup
+
+1. Ensure you're in the project directory
+2. Install required Python packages:
+   ```
+   pip install -r requirements.txt
+   ```
+3. Start the Flask server:
+   ```
+   python app.py
+   ```
+
+## Usage
+
+1. Open your web browser and navigate to `http://localhost:3000` (or the port specified by your React setup)
+2. Enter an IMDB movie review in the text input
+3. Click "Analyze" to see the sentiment analysis results
+4. (Optional) Provide feedback on the analysis accuracy
+
+## Project Structure
+
+- `/src`: React frontend source code
+- `/public`: Public assets for the frontend
+- `/backend`: Flask backend code
+- `/models`: Trained machine learning models
+- `/data`: Dataset and data processing scripts
+- `requirements.txt`: Python dependencies
+- `package.json`: Node.js dependencies
+
+## Dataset
+
+This project uses the IMDB Dataset of 50K Movie Reviews, available on Kaggle:
+[IMDB Dataset](https://www.kaggle.com/datasets/lakshmi25npathi/imdb-dataset-of-50k-movie-reviews)
+
+## Models and Performance
+
+| Model               | Accuracy |
+|---------------------|----------|
+| Gaussian NB         | 0.7379   |
+| Random Forest       | 0.7997   |
+| Logistic Regression | 0.82     |
+| LSTM                | 0.7424   |
+| Transformer         | 0.5      |
+
+## Contributing
+
+Contributions to this project are welcome. Please fork the repository and submit a pull request with your changes.
+
+## License
+
+[MIT License](LICENSE)
+
+## Contact
+
+Developer: Saquib
+GitHub: [saquib34](https://github.com/saquib34)
+
+## Acknowledgments
+
+- IMDB for providing the dataset
+- Kaggle for hosting the dataset
+- All open-source libraries and tools used in this project