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This project was created to address the problem of determining the rating of a restaurant on Zomato. By using machine learning, we are able to predict the rating of a restaurant based on various features such as location, cuisine, and price range. The resulting model is then deployed as a web application using Python and Streamlit, allowing users t

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Ag994/zomato-streamlit-Rating-Predtiction-Using-ML

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Zomato Rating Prediction App

This project uses machine learning, Python, and Streamlit to create a web application that predicts the rating of a restaurant on Zomato.

Streamlit App

Requirements

Python 3.6 or higher Streamlit Other required Python packages (e.g. scikit-learn, pandas)

Installation

Clone or download the repository Install the required packages: Copy code pip install -r requirements.txt

Usage

To run the app, navigate to the directory where the app.py file is located and run:

Copy code streamlit run app.py The app will then be accessible at http://localhost:8501.

Data

The data used in this project is available in the data directory. It consists of information on restaurants and their ratings on Zomato.

Model Training

The machine learning model is trained using the train.py script. The training data is loaded from the data directory and the trained model is saved to the models directory.

About

This project was created to address the problem of determining the rating of a restaurant on Zomato. By using machine learning, we are able to predict the rating of a restaurant based on various features such as location, cuisine, and price range. The resulting model is then deployed as a web application using Python and Streamlit, allowing users t

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