FarizMulya

Yosef Teofani Tamba NIM: 52250007

Plotting the Choropleth of Renewable energy share - with interactivity. Interactivity includes zoomability & tooltips when hovering. Tooltips shows, country name, Renewable Energy share %, GDP & year

This project builds a practical, end-to-end pipeline to predict employee attrition using supervised learning. After a focused EDA and careful feature engineering (including tenure/stability ratios), we compare multiple models via stratified 5-fold CV and select a regularized logistic regression that generalizes well (ROC–AUC ≈ 0.82). We address class imbalance with threshold tuning, improve probability reliability with isotonic calibration, and choose a business-aligned operating point by minimizing expected cost of false negatives vs. false positives. The result is an interpretable, lightweight model with clear HR actions and reproducible artifacts.

Various types of Kernel in SVM

Hồ Trần Hoàng Triều (2321000368) Nguyễn Trung Hậu (2321000319)

Clase 2 del curso de Matemática Actuarial II de la Maestría en Ciencias Actuariales Aplicadas de la Escuela de Educación Continua de la Universidad Galileo. Guatemala.