This project is part of the Data Science Capstone and focuses on building a predictive text model that suggests the next word based on a user's input. Using a large corpus of English text from blogs, news articles, and Twitter, the model was trained using n-gram tokenization and a Stupid Backoff algorithm to handle different context levels.

This report presents an exploratory data analysis (EDA) for the Data Science Capstone Project, based on text data from three sources: blogs, news, and Twitter. The primary objective is to understand the structure and content of the datasets in preparation for building a predictive text model.