Fantasy Open Wheel Challenge 2025 Thermal Race and Driver Picks

Education Apostolate by Municipality

A flexdashboard of machine learning models used for prediction of distance to the nearest brood tree using a data set from 1993.

Eldely Sister House by Municipaly

1.6 Lab Assignment

This project aims to predict heart disease using machine learning models based on key cardiovascular health indicators. The dataset, sourced from Kaggle, includes 11 features related to patient health. Various classification models, including Logistic Regression, Decision Tree, Random Forest, and Neural Networks, were trained and evaluated. The Random Forest model achieved the highest accuracy (85.5%). To further improve performance, an ensemble model combining Logistic Regression, Random Forest, and Neural Networks was implemented, increasing accuracy to 89.6%. The project highlights the effectiveness of machine learning in medical diagnosis and the impact of ensemble learning on predictive performance.