Exercise on analysis and prediction over the IBM Watson HR-Employee-Attrition Dataset. The goal was to predict the Attrition for employees. An Exploratory Data Analysis was done to check variables' correlation and strength of association, a class imbalance was detected and a logistic regression model was built and tested. Main conclusion is that the class imbalance, even after trying to solve it with sampling techniques, made difficult to fit a good model to predict Attrition and more data is needed.

The application described here is the final project for the “Developing data products” course part of the “Data Science specialization”

This report is my submission for the "Peer Assigment 2" on the Reproducible Research Course By Johns Hopkins Unversity on Coursera.org. In this report we analyze the U.S. National Oceanic and Atmospheric Administration's (NOAA) storm database. This analysis shows the most harmful weather events across the United States in terms of population health and greatest economic consequences. The analysis finally shows that with respect to population health, tornados events produce the most harmful impact to population health, followed by storms events; while the worse consecuences for economy measured on costs for crops and properties, are caused by Floods and Tornados.