Heart_Disease_Prediction_using_machine_learning

This project uses Heart disease prediction dataset from UCI to perform a classification task and predict a heart disease given other features.

Following machine learning models are compared:

• Logistic Regression
• KNeighbors classifier
• Random Forest classifier
• XGBoost

Following steps are performed in this project:

• Dataset preprocessing
• EDA
• Model Building
• Model hypertuning
• Model Evaluation
• Model Comparison
• Feature Importances
• Conclusion