The US Cancer Statistics Explorer is an interactive Shiny application that allows users to: - Explore estimated new cancer cases by state - Explore estimated cancer deaths by state - Compare cases and deaths visually - Calculate an estimated death rate for selected cancers The application was created to make national cancer statistics easier to explore through an interactive interface.

This project develops a predictive text model using Natural Language Processing techniques. The application predicts the next word based on user input and is deployed as a Shiny app. The project uses the SwiftKey dataset and demonstrates text mining, data analysis, and language modeling

Exploratory analysis of the SwiftKey text prediction dataset including blogs, news, and Twitter data. This report summarizes key findings and outlines the prediction model plan.

Exploratory analysis of the SwiftKey dataset for the Johns Hopkins Data Science Specialization Capstone Project.

Module 15 for GEOG 6680 at the University of Utah

A frog falls into a 50-meter-deep hole. Each day it climbs up 2 meters, and each night it slides down 0.5 meters. How many days does it take to climb out of the hole? Draw a related diagram.