This project applies Machine Learning techniques to predict the likelihood of heart disease based on patient health records. It includes:

Data preprocessing & feature selection

Supervised learning models (Logistic Regression, Decision Tree, Random Forest, SVM)

Unsupervised learning (KMeans, Hierarchical Clustering)

Hyperparameter tuning with GridSearchCV & RandomizedSearchCV

Model export (.pkl format) for deploymen