Movie Review Sentiment Analysis using NLP

Project Overview

Developed a sentiment analysis application for movie reviews utilizing NLP techniques, Sklearn feature extraction, and Pandas for data processing. Deployed the model with Streamlit, and used the Pickle library for efficient model serialization.

Installation Guide

Prerequisites

Ensure you have Python installed on your system. It is recommended to use PyCharm for an optimal development experience.

Steps to Install

1. Clone this repository:

   git clone https://github.com/your-username/movie-review-sentiment-analysis.git
   cd movie-review-sentiment-analysis

2. Create a virtual environment (recommended):

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

3. Install necessary dependencies

Running the Application

1. Navigate to the project directory.
2. Run the Streamlit application:

   streamlit run app.py

Successful Project Demonstration

Sentiment Analysis of Positive Movie Review

Sentiment Analysis of Negative Movie Review

Conclusion

This project successfully demonstrates the implementation of NLP-based sentiment analysis for movie reviews. By leveraging Sklearn, Pandas, and Streamlit, we created an efficient and interactive web application for analyzing sentiments.

Thank you for exploring this project! Feel free to contribute and share your feedback.

Sourav Singh