Anggota: 1. Adinda Adelia futri (52250055) 2. Angelica Florentina (52250063) 3. Boma Satrio (52250061) 4. Chricyesia Winnerlady F. Uvas_52250075

subtitle: "WQD7004 – Programming for Data Science Project" author: "Group 3 | Occurrence 1" date: "18 January 2026" Project Background : Our organization, a large Infrastructure & Asset Management Firm, manages a diverse portfolio of properties across varying climates. With the increasing frequency of extreme weather events, the Chief Information Officer (CIO) has mandated a 10-week initiative to develop a data-driven Flood Risk Prediction Framework. This project aims to transition our risk management strategy from reactive repairs to proactive asset protection.

An analysis of the U.S. National Oceanic and Atmospheric Administration's (NOAA) storm database for the Reproducible Research course from John Hopkins University on Coursera.

This presentation explains the design and working of a Shiny web application for predicting the next word using N-gram language models, developed as part of the Coursera Data Science Capstone Project.