Ranking Model

Overview

The Ranking Model repository is a machine learning project developed to address the AiHello Hackathon Challenge. It focuses on building a model that ranks candidates based on specific criteria, leveraging advanced algorithms and data processing techniques.

Features

• Data Processing: Scripts and tools for cleaning and preparing data for modeling.
• Model Training: Implementation of machine learning models to rank candidates effectively.
• API Integration: Endpoints to access the model's predictions programmatically.
• Visualization: Notebooks and scripts for visualizing data and model performance.

Repository Structure

• data/: Contains datasets used for training and evaluation.
• model/: Includes trained models and related assets.
• notebooks/: Jupyter notebooks for exploratory data analysis and model development.
• src/: Source code for data processing and model implementation.
• api/: Flask application providing API endpoints for model inference.
• requirements.txt: List of dependencies required to run the project.

Getting Started

Prerequisites

• Python 3.8 or higher
• pip package manager

Installation

1. Clone the repository:

   git clone https://github.com/isatyamks/ranking_model.git
   cd ranking_model

2. Install dependencies:

   pip install -r requirements.txt

3. Set up environment variables:

   • Create a .env file in the root directory.
   • Add necessary environment variables as specified in the project documentation.

Usage

• Data Processing:

  • Run data preprocessing scripts located in the src/ directory to prepare the dataset.

• Model Training:

  • Use the notebooks in the notebooks/ directory to train and evaluate models.

• API Deployment:

  • Navigate to the api/ directory and run the Flask application:

    python app.py

  • Access the API endpoints as documented to get model predictions.

Related Repositories

• Frontend Repository: Frontend Interface

  • A web-based interface allowing users to interact with the ranking model seamlessly.

• Backend Repository: Backend Services

  • Handles data management, authentication, and integrates with the ranking model API.

These repositories collectively form the complete application, providing a user-friendly frontend, a robust backend, and the machine learning ranking model.

Preview Submission Demo

• Demo Link: Preview Submission

Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your changes. Ensure that your code adheres to the project's coding standards and includes appropriate tests.

License

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

---

For any questions or support, please open an issue in this repository.