Machine Learning Project : KEEP IT BEATING
Coronary Heart Disease (CHD) is a major global concern, responsible for substantial portion of cardiovascular-related morbidity and mortality. Early detection of CHD is paramount for prompt intervention and prevention efforts.
The main objective of this project is to leverage the power of machine learning techniques to identify people who are at risk of developing CHD within 10 years, so that appropriate medical intervention processes can be promptly administered.
01 Data Wrangling : Understanding the dataset and cleaning the data
02 EDA : Univariate and Bivariate analysis
03 Feature Engineering : Creating variable interactions based on secondary research and EDA
04 Modelling & Validation : Training multiple models and validating them, then comparing the models to arrive at the best one
05 Recommendations : The lifestyle changes to make to reduce changes of heart disease
06 Enhancements : Ensemble the models
● Build a voting classifier which is an ensemble of different ML models used to improve performance
● Leverage advanced techniques like SVM, Neural networks to improve prediction power
● Explore external data sources