This module explores the package data.table in R.

Monserrat Rivera y Diana Gonzalez

Consolidated budge for Inner Combat Training Program

Muzaffer Enes Ertaş

This is the R Markdown file compiled to meet the specifications of IE2341 Assignment 2 Question 3.

Composite z-score based on diabetes-correlated health indicators.

Muzaffer Enes Ertaş

This project delivers an interactive text-prediction web application built using R and Shiny, satisfying the final capstone requirement for the Johns Hopkins Data Science Specialization. The application utilizes a highly compressed N-gram natural language model (built from blogs, news, and Twitter text data) and implements an efficient "Stupid Back-off" algorithm to predict the next word dynamically as a user types. The entire system is engineered for low latency and a minimal memory footprint, making it ideal for deployment on standard web environments or mobile devices. Included are the links to the live, operational interactive Shiny application hosted on shinyapps.io, alongside a compiled 5-slide markdown presentation pitching the data pipeline, algorithm structure, and performance metrics of the tool.