readme.md

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

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

Contact

Developer: Saquib GitHub: saquib34

Acknowledgments

• IMDB for providing the dataset
• Kaggle for hosting the dataset
• All open-source libraries and tools used in this project