# Text to numbers: label encoding, one-hot, BoW and TF–IDF

Subject: Natural Language Processing

Exam: TEE

Reader: https://deep-learning-study-room.vercel.app/nlp/#tee/read/u2-representation

Canonical: https://deep-learning-study-room.vercel.app/read/nlp/tee/read-chapter/u2-representation/

TEE · Unit 2 PDF pages 51–92

1. [Vocabulary and vectors—what each coordinate means](https://deep-learning-study-room.vercel.app/read/nlp/tee/read/u2-representation--u2-vocab/)
2. [Label and one-hot encoding: three complete examples](https://deep-learning-study-room.vercel.app/read/nlp/tee/read/u2-representation--u2-label-onehot/)
3. [Bag of words and bag of n-grams](https://deep-learning-study-room.vercel.app/read/nlp/tee/read/u2-representation--u2-bow/)
4. [TF–IDF from the exact slide convention](https://deep-learning-study-room.vercel.app/read/nlp/tee/read/u2-representation--u2-tfidf/)
5. [Combined slide numerical: TF–IDF followed by cosine](https://deep-learning-study-room.vercel.app/read/nlp/tee/read/u2-representation--u2-slide-combined/)