This application utilizes a predictive text model based on word frequency and context that reduces the number of required keystrokes for next word entry. This is a Coursera / Johns Hopkins Data Science Specialization Capstone project.

Milestone Report for Data Science Course

HTML Version - since Rpres not accepting plotly charts The purpose of this presentation is to: - Use time-series data from Quandl - Create an interactive chart using Plotly - Illustrate the case against buying APPL shares - Quickly publish online via the RPubs service

The purpose of this presentation is to: - Use time-series data from Quandl - Create an interactive chart using Plotly - Illustrate the case against buying APPL shares - Quickly publish online via the RPubs service

Here's a quick leaflet map in R for meeting people to dance salsa with in your community. The map connects to the Spanish-speaking groups that are part of the Salsa Social network.

This one-of-a-kind Shiny application has multiple benefits. It 1. Provides a faster, better, cheaper way to sort through Twitter friends 2. Uses best of open source R community with IBM's Watson API data, and 3. Combines personality and social media research - a growing data science market. Demo: https://rudymartin.shinyapps.io/Watson-TweetlyzR

This document describes an analysis done as an assignment of the Coursera Reproducible Research Course from Johns Hopkins University. Storms and other severe weather events can cause both public health and economic problems for communities and municipalities. Many severe events can result in fatalities, injuries, and property damage. Preparing for unprecedented extreme weather is a key concern of public officials.