Around the world, people are spending an increasing amount of time on their mobile devices for email, social networking, banking and a whole range of other activities. But typing on mobile devices can be a serious pain. SwiftKey builds a smart keyboard that makes it easier for people to type on their mobile devices. One cornerstone of their smart keyboard is predictive text models. In this project, we will use our knowledge of Data Science in order to clean and analyze data, building and sampling predictive text models and finally use basics of Natural Language Processing for predicting text output from users in order for them to type on their mobile devices with ease.

The prediction application has been designed to predict the Volume of the tree based on the details of Girth of the Tree provided by the user. The application has been uploaded at the following link. <https://vedantmane.shinyapps.io/predictionapp/>

A web page using R Markdown that features a map created with Leaflet.

Exploring the U.S. National Oceanic and Atmospheric Administration’s (NOAA) storm database - Health and Economic Impacts 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, and preventing such outcomes to the extent possible is a key concern. 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, and property damage. This report gives us a brief idea about the weather events in the United States that cause major destruction of life and property within the country.