A real-time predictive text system that suggests the most likely next word in a sentence.

This project explores large text datasets from blogs, news articles, and Twitter. The goal is to understand the structure and characteristics of the text data before building a predictive text model. This analysis focuses on basic statistics such as number of lines, word counts, and text distribution patterns.