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This report presents the complete methodology, implementation, and evaluation of a next-word prediction system built as the final capstone project for the Johns Hopkins Data Science Specialization on Coursera. The project was developed using three large English-language text corpora drawn from blogs, news articles, and Twitter posts, collectively comprising over 580 MB of raw text and approximately 4.27 million lines.

The goal of this project is to build a predictive text model using the SwiftKey dataset provided for the Johns Hopkins Data Science Capstone. The dataset contains text from blogs, news articles, and Twitter posts.