Proxipense! The next generation in next word predictive analytics. This application is the capstone project for the Johns Hopkins Data Science Specialization on Coursera

This is a milestone report for the Coursera Capstone project, an Natural Language Processing (NLP) analysis. The report discusses (1) How do download and load the project data (2) Presents basic summary statistics about the datasets (3) Reports uninteresting findings (4) Requests peer feedback on project plans

The Interactive World Bank Project Map is a Shiny application that allows users to see project relative project funding volumes plotted according to their respective project implementation countries, over time.

The following table is a discussion of variables in the R mtcars dataset. It was developed in response to the Coursera Regression Models class taught by Prof. Brian Caffo for the course project assignment: “You work for Motor Trend, a magazine about the automobile industry. Looking at a data set of a collection of cars, they are interested in exploring the relationship between a set of variables and miles per gallon (MPG) (outcome). They are particularly interested in the following two questions: ‘Is an automatic or manual transmission better for MPG’ and ‘Quantify the MPG difference between automatic and manual transmissions’”

##Synopsis This is an analysis of US weather events from 1950 to 2011 using the NOAA Storm Database to answer to questions: (1) Across the United States, which types of events are most harmful with respect to population health? (2) Across the United States, which types of events have the greatest economic consequences? The analysis looks at these questions with respect to the magnitude of storm events with respect to the frequencies of occurances and the magnitude of damage, whether in human or economic terms. The analysis also examines the distribution of these types of storm events in terms of the number of US states where this type of event has been recorded. The analysis finds key differences in event magnitude when examined in terms of human or economic costs, but identifies the most serious weather events as: Floods, Hurricanes, Tornadoes, Heat Waves and Thunderstorms.