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Chris McCormick introduces Episode Three of his Burt research series, where he explores the Burt tokenizer and word embeddings. He explains how Burt handles out-of-vocabulary words and the basics of word embeddings. In this episode, he applies Burt to a text classification task to demonstrate its practical use. The goal is to understand the application of Burt and learn about its internal architecture. More in-depth discussions on Burt's architecture will be covered in future episodes.
