Brief technical overview of SBO natural language processing algorithm implementation to be used for next word in phrase predictions. Work done for Capstone Project of Coursera Johns Hopkins Data Science Sjpecialist Certificate

Redone data analysis of text documents using Quanteda instead of tm for Coursera Capstone project June 2018

Exploratory data analysis of document texts in preparation for developing algorithms to predict word sequences. Created as part of Capstone Project for the Johns Hopkins School of Public Health Data Science Specialization Certificate offered through Coursera. June 2018.

Submitted for Coursera Reproducible Research Course Peer Reviewed Project 2, June 2017 This project involves exploring the U.S. National Oceanic and Atmospheric Administration's (NOAA) storm database. This database tracks characteristics of major storms and weather events in the United States, including when and where they occur, as well as estimates of any fatalities, injuries, property damage and crop damage. The data is used to examine health and economic consequences of adverse weather related events. Health consequences are measured in terms of counts of storm caused casualties (fatalities + injuries) and economic consequences are measured as the total cost of property and crop damage.