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Understanding Word Embeddings: How Machines Learn the Meaning of Words

When I started learning Natural Language Processing (NLP), one question kept coming back to me: How can a computer understand words when words are just text?

  • Word embeddings represent words as numerical vectors for computers to understand word relationships.
  • Word2Vec limitations include reliance on training corpus quality and potential bias inheritance.

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