// ⬡ Deep Learning Foundations
Word2Vec
Learns word vectors by predicting words from context.
Word2Vec 词向量 2013 Beginner core
IN PLAIN WORDS
Maps each word to a dense vector so words in similar contexts are close, giving king − man + woman ≈ queen. It popularized embeddings.
Used in: Word embeddings, item2vec recommenders
TIMELINE · prerequisites → this → what builds on it
01Original paper
Efficient Estimation of Word Representations in Vector Space
Tomas Mikolov, Kai Chen, Greg Corrado, et al. · 2013
arXiv ↗ ✓ Verified · arXiv API
02Where it sits
Learn the left column first; the right column builds on this one.
Related:Byte-Pair Encoding (BPE) TokenizationSentence Embeddings (Sentence-BERT)
Left: prerequisites · right: builds on this · dashed: related. Full map →
03Learning resources
Official docs, explainers, courses and reference code. All links checked.
04Where the course teaches it
On learning paths:Zero to Deep LearningUnderstanding an LLM End to End
For AI / data
- Verification: verified, checked 2026-10-21.
- JSON: /api/learn/algorithms.json (id:
word2vec)