Restaurant Feedback Sentiment Analysis

Welcome to the Restaurant Feedback Sentiment Analysis project! This repository utilizes Natural Language Processing (NLP) techniques to provide valuable insights from customer feedback for restaurants. Enhance your restaurant's services and dining experience by understanding customer sentiments.

Table of Contents

• About the Project
• Getting Started
• Installation
• Usage
• Features
• Contributing
• License
• Contact

About the Project

Customer feedback is a goldmine of information for restaurant owners. This project leverages NLP to analyze feedback, providing detailed sentiment insights. Improve your restaurant's reputation and customer satisfaction by acting on these insights.

Getting Started

These instructions will help you get a copy of the project up and running on your local machine for development and testing purposes.

Installation

1. Clone the repository:

   git clone https://github.com/20481A5450/Analyzing-Customer-Feedback-For-Restaurants.git

Usage

1. Collect customer feedback data and place it in the 'zomato.csv' file.

2. Run the analysis script:

   python main.py

3. Explore the sentiment analysis results and improve your restaurant accordingly.

Features

• Sentiment analysis of customer feedback.
• Actionable insights to enhance restaurant services.
• Easy-to-use and customizable for different restaurant businesses.

Contributing

We welcome contributions from the community. Feel free to fork the project, create your own branch, and submit a pull request with your improvements.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

If you have any questions or suggestions, please feel free to reach out to us:

• Shaik.Zohaib- shaikzohaibgec@gmail.com
• Project Link: https://github.com/20481A5450/Analyzing-Customer-Feedback-Sentiment-For-Restaurants