Predicting HDL Cholesterol using Machine Learning & Deep Learning
Rolando Vargas, Eleniz Espina, Bryce Leister | University of Miami | MAS 635
This project predicts HDL (High-Density Lipoprotein) cholesterol levels using demographic, dietary, behavioral, and body measurement variables from the NHANES dataset. We implement and compare 7 baseline ML models and 2 deep learning architectures.