Text Preprocessing (Tokenization, Stemming, Lemmatization)

Summary

Turning raw text into a cleaner, more analyzable form — tokenization splits text into words/subwords, stemming crudely chops word endings, lemmatization properly reduces words to their dictionary root.

• 1Tokenize a sample paragraph and inspect the resulting tokens.
• 2Compare stemming and lemmatization on the same set of words and note the differences.
• 3Learn when heavy preprocessing helps (classic ML) versus when it can hurt (modern transformer models).