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Zomato Bangalore Restaurants Rating Prediction

This project predicts restaurant ratings in Bangalore using machine learning techniques.

Overview

This repository contains the code for predicting restaurant ratings in Bangalore using various machine learning models. The project involves data ingestion, preprocessing, model training, and deployment of a web application for user interaction.

Libraries Used

The project relies on several Python libraries, all of which are listed in requirements.txt. To install the dependencies, run:

pip install -r requirements.txt

• pandas: Data manipulation and analysis.
• numpy: Numerical operations on arrays and matrices.
• seaborn, matplotlib: Data visualization libraries.
• scikit-learn: Machine learning toolkit for data mining and analysis.
• xgboost: Gradient boosting library for optimized distributed gradient boosting.
• flask: Micro web framework for building web applications in Python.
• dill: Serialization library for Python objects.
• streamlit: Open-source app framework for machine learning and data science projects.

Project Structure

Files and Directories

• setup.py: Project setup details.
• requirements.txt: Dependency list for easy installation.
• source/logger.py: Logging configuration for the project.
• source/exception.py: Custom exception handling for error tracking.
• .gitignore: Specifies files and directories ignored by Git.
• README.md: General project information and setup instructions.
• data/: Directory for dataset storage.
• source/: Source code directory.
  • __init__.py: Enables module usage.
  • source/components/data_ingestion.py: Manages data ingestion from various sources.
  • source/components/data_transformation.py: Handles data preprocessing and transformation.
  • source/components/model_trainer.py: Trains machine learning models and performs hyperparameter tuning.
  • source/pipeline/prediction_pipeline.py: Creates a web application using app.py and utils.py.
  • source/utils.py: Stores common functions used throughout the project.
  • application.py: Streamlit application for user interaction and prediction.

🚀 Run Locally

To run this project locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/Lavishgangwani/iNeuron-RestaurantRatingPredictions.git

2. Navigate into the project directory:

   cd iNeuron-RestaurantRatingPredictions

3. Create and activate a virtual environment:

   python -m venv myenv
   myenv\Scripts\activate (Windows)
   source myenv/bin/activate (Mac/Linux)

4. Install dependencies:

   pip install -r requirements.txt

5. Run the Streamlit application:

   streamlit run app.py

6. Open a web browser and go to the local Streamlit URL provided after running the above command to use the application locally.

Deployment

The project is deployed using Streamlit and can be accessed publicly via the following link: Zomato Bangalore Restaurants Prediction App.

🎯 Project Created by

Lavish Gangwani
Email: [email protected]

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