An Intuitive Application that Predicts the next Word! Word Predictor can be implemented on mobile devices and offers advantages over standard text typing.

This report, submitted in partial fulfillment of the requirements of the Coursera course, “Data Science Capstone”, concerns the R package “wordprediction”, which contains functions for an auto-completion model that predicts the next word to be typed based on a word or phrase previously typed. The source code can be found at https://github.com/Barkia/Final-Project-Submission, a presentation at http://rpubs.com/Barkhia/wordprediction, and a demonstration at https://ahmedbarkhia.shinyapps.io/word-prediction/. Auto-completion is a common function on mobile devices. As a user types, an auto-completion function presents that user with possible completions to the current word being typed or probable words that could follow the current word or phrase after it is typed. The package “wordprediction” provides the latter function.

The Capstone project for the Coursera Data Science Specialization involves using the HC Corpora Dataset. The Capstone project is done in collaboration with Swiftkey and the goal of this project is to design a shiny application with text prediction capabilities. This report will outline the exploratory analysis of the dataset and the current plans for implementing the text prediction algorithm.

The purpose of this slidify presentation is to pitch the Diamonds Explorer Shiny application built for the Coursera Developing Data Products course.

In this report, we will analyze `mtcars` data set and explore the relationship between a set of variables and miles per gallon (MPG). The data was extracted from the 1974 *Motor Trend* US magazine, and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973–74 models).

This report address questions related to Weather Events and Storms in U.S. that are most damaging in terms of Fatalities, Injuries and damages to properties and crop. The two mainly questions to be answered are: 1 - Which types of events are most harmful with respect to population health? 2 - Which types of events have the greatest economic consequences?