An AI-powered web application that predicts employee attrition using Machine Learning. Built with XGBoost and SMOTE to help HR teams identify at-risk employees and take proactive retention measures.
- 🔍 Single Prediction — Predict attrition for individual employees
- 📂 Bulk Prediction — Upload CSV to predict multiple employees at once
- 💡 HR Recommendations — Actionable retention strategies
- 🏢 Company Benefits — Tailored benefit suggestions to retain talent
- 📈 Probability Score — Visual stay/leave probability bar
| Tool | Purpose |
|---|---|
| Python | Core language |
| Streamlit | Web application framework |
| XGBoost | Prediction model |
| SMOTE | Handle class imbalance |
| Scikit-learn | Preprocessing & evaluation |
| Pandas & NumPy | Data handling |
| Matplotlib | Data visualization |
git clone https://github.com/Pramod-Ray/Employee-Attrition-app.git cd Employee-Attrition-app pip install -r requirements.txt streamlit run ab.py
Employee-Attrition-app/ │ ├── ab.py # Main Streamlit application ├── Employee-Attrition.csv # Training dataset ├── requirements.txt # Dependencies └── README.md # Project documentation
Pramod Ray
GitHub