“Before machines can understand us, they need to know where one word ends and another begins.” 🧠 Introduction: Why Tokenization Matters Natural Language Processing (NLP) has made astounding progress—from spam filters to chatbots to sophisticated language models like GPT-3. But at the heart of every NLP system lies a deceptively simple preprocessing step: tokenization. Tokenization is how raw text is broken into tokens—units that an NLP model can actually understand and process. Without tokenization, words like “can’t”, “data-driven”, or even emoji 🧠 would remain indistinguishable gibberish to machines. This blog dives into what tokenization is, the types of tokenizers, the…