To build a web application that supports online prediction using trained machine learning model and pipeline based on metrics such as age, sex, smoker etc
The primary language for modelling and data analysis is Python. Pycaret library was used to perform automated preprocessing steps as well as conducting model comparisons. Streamlit was used to create the webapp and deployed on Github via streamlit sharing.
This dataset was taken from Kaggle which contains information about patients such as demographics and basic health risk metrics at the time of hospitalisation.