Tokenization in NLP Explained: Transforming Text into Insights (Part 2 - Advanced Techniques)

Building on the foundation laid in the first part of our series, where we covered the basic techniques for tokenization in NLP, let’s now look at some of the more sophisticated ways of doing tokenization. In this second part, we will explore the cutting-edge techniques like Byte-Pair Encoding (BPE), Subword tokenization, and beyond. These methods are designed to tackle more complex aspects of language processing, allowing machines to better grasp the subtleties of human language. They are great at handling new words, reducing the size of vocabulary and adapting to the linguistic diversity. Let’s examine each of these methods, along with their pros and cons and practical implementations.