Phase 10 · NLP & Modern AI
TopicsBag of Words & TF-IDF
Part of the Data Science Roadmap.
Summary
Classic text representation methods — Bag of Words counts word occurrences, TF-IDF weights words by how distinctive they are to a document versus the whole corpus — simple, fast, and still useful baselines.
How to Learn This
- 1Build a Bag of Words representation for a small set of sample documents.
- 2Compute TF-IDF scores and identify the most 'distinctive' words per document.
- 3Learn why TF-IDF often outperforms raw word counts for text classification.
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Text Preprocessing (Tokenization, Stemming, Lemmatization)
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Word Embeddings (Word2Vec, GloVe)
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