AI-powered employee attrition prediction with SHAP explainability

HR Analytics Dashboard | Attrition Prediction | Power BI Style | HR Assistant

Prédiction du taux d'attrition RH pour HumanForYou. Projet d'Analyse de Données (EDA) et de Machine Learning pour identifier les facteurs de turnover des employés. (Projet Ingénieur A4)

Employee Attrition Prediction - Predictive Systems project in AI / ML / GenAI for CSEProjects360 final year project catalog.

End-to-end people analytics system identifying at-risk employees with 96% AUC accuracy. Covers the full pipeline — data engineering, ML modeling, SHAP explainability, and an interactive dashboard with segment analysis and a retention What-If simulator.

A production-ready machine learning pipeline and interactive Streamlit dashboard for predicting employee attrition. Features an automated preprocessing pipeline, SMOTE-based class balancing, XGBoost modeling, and SHAP-based interpretability for proactive HR talent management.

A Streamlit-based web app that predicts employee attrition using machine learning. Upload employee data and get instant predictions on who is likely to leave.

Predicting participant dropout in longitudinal research studies using logistic regression

Multi-signal machine learning system for employee attrition risk modeling using structured HR data, behavioral communication drift, and neural meta-learning fusion.

Predicting employee attrition with ML — AUC 0.774 | Python, Scikit-Learn, Gradient Boosting

AURA (Attrition Understanding & Retention Analytics) is an interactive HR analytics web application designed to help organizations understand and predict employee attrition. The platform combines data visualization, predictive analytics, and AI-driven insights to identify employees at risk of leaving and uncover the key factors driving attrition.