As part of a course project (Engineering Analytics), I implemented machine learning classifiers (Random Forest, Support Vector Classifier, Logistic Regression, Linear Discriminant Analysis) to predict cardiovascular disease using medical patinet data. The model achieved 72% accuracy on gender-specific classes, addressing fairness and bias considerations in prediction.