Heart Disease Prediction Using Machine Learning

Developed a machine learning model to predict the likelihood of heart disease using patient medical data such as age, blood pressure, cholesterol, heart rate, and other health indicators. Applied data preprocessing, feature selection, model training, and performance evaluation to achieve accurate predictions. Used Python libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib for analysis and visualization. This project helps support early diagnosis and healthcare decision-making.