Scikit-Learn

Machine learning can predict the survival of patients with heart failure from serum creatinine blood levels and heart ejection fraction alone.

Frequently the hardest part of solving a machine learning problem is finding the right estimator for the job.

The focus of this analysis is to build a predictive tool that strives to determine the features of posts that are likely to cause user engagement on social media.

This data analysis generates a predictive model that can forecast the agents that may be responsible for unplanned hospital readmissions of people affected by diabetes.

This project aims to understand which distinct conditions and characteristics were to blame for the buildings that sustained the most damage from the massive 2015 Gorkha earthquake in Nepal.