Rest_Model_Interface

Developed by Pirate-Emperor, Rest_Model_Interface is a simple web application that provides seat forecasting using a machine learning (ML) model. It is built using Flask, a lightweight web application framework in Python.

Features

• Seat Forecasting: Generates seat forecasting based on user input and preferences.
• Cluster Identification: Generating clusters of restaurats based on dishes and customers based on frequency, recency, cost, and head count.
• Hybrid Model: Use of both clustering and forecasting to predict reserve seats based on MVP customer cluster
• ML Model Integration: Utilizes a pre-trained ML model for predicting user preferences.
• User Interface: Offers a clean and easy-to-use web interface for users to interact with the application.
• Search Functionality: Allows users to search for movies based on keywords or titles.
• User Authentication: Provides a secure user authentication system for personalized recommendations.

Prerequisites

To run the project, you will need:

• Python 3.x
• Required Python libraries (Flask, numpy, pandas, scikit-learn, etc.)

Installation

Clone the repository and navigate to the project directory:

git clone https://github.com/Pirate-Emperor/Rest_Model_Interface.git
cd Rest_Model_Interface

Install the required Python packages:

pip install -r requirements.txt

Usage

Run the Flask app:

python app.py

The web application will be running on http://127.0.0.1:5000/.

Visit the URL in your web browser and start exploring the seat forecasting.

Data Source

The project uses a dataset of movie information and user ratings to train the ML model.

Development

To enhance the project, you can modify the Python scripts and HTML templates in the src and templates directories, respectively. Some potential areas for improvement include:

• Improving the accuracy of the ML model for better recommendations.
• Enhancing the user interface design for a more engaging experience.
• Incorporating additional features, such as movie trailers or reviews.
• Scaling the application for handling a larger number of users and data.

License

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