Child mortality is a very acute problem faced by mankind from time immemorial, and demographers have used traditional methods to derive inferences. However, with advances in computing and thereby in the machine learning space, new avenues have been opened to determine the various causal factors at a faster pace. This project is another step in that direction by employing machine learning models to traditional sampled data based out of India and including the socio-economic and medical variables together.

The objective is that the generated insights can provide input to policymakers to determine the best ways to formulate socio-welfare schemes and thereby reduce the child mortality count in India.