Python 3.7 and R are used in this project, and files with .ipynb extension should be opened with jupyter notebook to run them.
This project uses machine learning to analyze National Health and Nutrition Examination Survey. Our data set consists of 15,944 observations. There are three steps: data preprocessing, feature engineering, and modeling. More details can be found in folders.
