What is token usage in NLP?
Token usage in NLP refers to how text is broken down into smaller units called tokens, which can be words, phrases, or symbols.
Why is tokenization important in NLP?
Tokenization is crucial because it helps in understanding the structure of the text, enabling better analysis and processing.
Can you give me examples of tokenization methods?
Sure! Common methods include whitespace tokenization, punctuation-based tokenization, and using libraries like NLTK or SpaCy.
How does tokenization affect machine learning models?
Tokenization impacts how models interpret text data, influencing their performance and accuracy in tasks like classification.
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