Employee Attrition Prediction

The Employee Attrition Prediction System uses machine learning and statistical analysis to predict employee turnover. Designed for HR professionals, it facilitates proactive decision-making to reduce attrition and enhance workforce management strategies.

Technologies Used

• Backend: Flask (Python)
• Frontend: HTML5, CSS3, JavaScript
• Containerization: Docker
• Machine Learning: Scikit-learn, XGBoost, Scipy, Seaborn, Matplotlib, Pandas, NumPy

Application Demo

Installation

Prerequisites

Ensure the following are installed on your local machine:

• Python 3.8+
• Docker (optional for containerized deployment)

Clone the Repository

git clone git@github.com:abdullahashfaq-ds/Employee-Attrition-Prediction.git
cd Employee-Attrition-Prediction

Method 01: Virtual Environment Setup

python -m venv venv
# On Windows, use:
venv\Scripts\activate
# On Linux/MacOS, use:
source venv/bin/activate
# To set up the production environment:
pip install -r requirements.txt
# To set up the development environment:
pip install -r requirements.dev.txt
# To run the project:
python app.py

Method 02: Docker Setup

For a containerized environment, build and run the container:

docker build -t employee-attrition .  
docker run -p 5000:5000 employee-attrition

Access the application at http://localhost:5000

License

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

Contact

For inquiries or support, please open an issue on GitHub or contact abdullahashfaq.ds@gmail.com.