heart disease prediction

build models that predict whether an individual has heart disease. By comparing multiple approaches, I explored which models perform best on structured medical data.

What I Did:

•Cleaned and preprocessed the dataset

•Handled categorical features with one-hot encoding

•Scaled numerical features

•Splitted the data into training and testing sets

•Trained and compared three models:

•Logistic Regression

•Random Forest Classifier

•Neural Network (Deep Learning)

Key Results

Model Accuracy Logistic Regression0.886

Neural Network0.880

Random Forest0.875