https://github.com/aleksdrophunter/employee-attrition-prediction-with-machine-learning
Employee Attrition Prediction with Machine Learning | Analyzing HR data to predict employee turnover using Random Forest. Includes EDA, feature engineering, model training, and evaluation. Achieved 90% accuracy.
https://github.com/aleksdrophunter/employee-attrition-prediction-with-machine-learning
attrition data-analysis data-science data-visualization employee machine-learning matplotlib numpy pandas python randomforestclassifier scikit-learn seaborn smote
Last synced: about 1 month ago
JSON representation
Employee Attrition Prediction with Machine Learning | Analyzing HR data to predict employee turnover using Random Forest. Includes EDA, feature engineering, model training, and evaluation. Achieved 90% accuracy.
- Host: GitHub
- URL: https://github.com/aleksdrophunter/employee-attrition-prediction-with-machine-learning
- Owner: AleksDropHunter
- Created: 2025-03-27T21:04:33.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2025-03-27T22:13:59.000Z (about 1 month ago)
- Last Synced: 2025-03-27T22:30:02.355Z (about 1 month ago)
- Topics: attrition, data-analysis, data-science, data-visualization, employee, machine-learning, matplotlib, numpy, pandas, python, randomforestclassifier, scikit-learn, seaborn, smote
- Language: Jupyter Notebook
- Size: 223 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0