Classifying Fetal health with Machine Learning
A comparative study of linear regression and decision tree to predict the child mortality rate based on other socioeconomic indicators from the World Bank.
Determining the most important predictors of diarrhoea in children under five in South and Southeast Asia by exploring the spatiotemporal association between diarrhoeal incidence and various behavioural, socio-demographic, and environmental factors.
This project involves exploratory analysis on data (child mortality rate) using Python. Then, creating a presentation with explanatory plots to communicate findings. (Udacity Project)
Australia SA3-level analysis of relationship between child mortality/morbidity and climate conditions/air pollution
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