University · Data Science · Natural Language Processing for Data Science
Word Embeddings: Word2Vec, GloVe, and Contextual Representations
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A rigorous treatment of dense word vector representations — from the distributional hypothesis and Word2Vec to GloVe's global statistics approach and the transition to contextual embeddings.
Inhaltsübersicht
- From Sparse to Dense: The Distributional Hypothesis
- Word2Vec: Skip-Gram and CBOW
- GloVe: Global Vectors for Word Representation
- Contextual Representations: ELMo and the Road to BERT
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