The goal of this project was to build a Machine Learning model to predict Septic shock in an emergency room environment using MIMIC3 database.

This projected was organized using an Modeling Pipeline which included all the stages in building a ML model. This included stages such as Predictive Target, Cohort Construction, Feature Construction, Feature Selection, Predictive Model, and Performance Evaluation.

The predictive models were constructed using scikit-learn, and included algorithms such as neural networks, decision trees, and AdaBoost.