Word2vec : A Deep learning approach of word embeddings
SMRTR summary
Word2Vec, developed by Google, turns words into numerical vectors that capture meaning and relationships — so math like "King − Man + Woman ≈ Queen" actually works. It uses two neural network approaches, CBOW and Skip-gram, to learn from raw text without labels, making it fast, memory-efficient, and widely reusable in NLP applications.
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