This project demonstrates a next-word prediction algorithm in a Shiny app. Users can type any phrase, and the app predicts the most likely next word. The app is accompanied by a 5-slide presentation on RPubs that explains the algorithm, usage instructions, and showcases the functionality.

This presentation introduces a Shiny application that visualizes the Old Faithful geyser waiting time data using an interactive histogram. The app allows users to adjust the number of bins dynamically and demonstrates reactive programming in R.

This project is a web-based presentation created using R Markdown. It includes the creation date and features an interactive data visualization built with the Plotly library. The presentation demonstrates how interactive plots can be embedded into slides and published online.

This project demonstrates the creation of a web page using R Markdown that includes an interactive map built with the Leaflet package. The document displays the creation date automatically and showcases basic map interactivity such as zooming and panning.

This report describes a Random Forest model used to predict how participants performed weight-lifting exercises using accelerometer data. The model achieved high accuracy on the validation set and predictions for 20 test cases are included

This milestone report presents a concise exploratory analysis of text datasets (blogs, news, and Twitter) for building a word prediction model. It includes summary statistics, initial findings, and plans for developing a predictive text Shiny application.