What Is Tokenization In Machine Learning?


Tokenization is a crucial step in language models as it breaks down text data into smaller units called tokens, such as words or characters. These tokens serve as a representation of the text and enable various NLP tasks. Tokenization helps standardize and process text data, making it easier to analyze. It also addresses language-specific challenges like stemming and stop-word removal, improving the accuracy of language models.

word embeddings with tokenization example

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