This 5-slide presentation explains the working and performance of a lightweight next word prediction app developed in R using Shiny. It covers the model pipeline, app UI, prediction logic using n-grams, and highlights real usage scenarios. The app demonstrates applied NLP techniques and serves as a solid foundation for more advanced predictive typing tools.

This project is part of the Coursera Data Science Capstone, focused on building a predictive text model using a large corpus of English text from blogs, news, and Twitter. The goal is to create a Shiny web application that suggests the next word a user is likely to type. This milestone report presents an exploratory data analysis of the training datasets. It includes summary statistics, basic text preprocessing, and initial visualizations to understand the structure and content of the data. The report also outlines the planned steps for building the prediction algorithm using n-grams and deploying it in an interactive Shiny app.