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3 cards from this section. Quick, good the night before a test.
What is the purpose of word embeddings?
Think about how machines understand language.
Name one architecture of Word2Vec.
Consider how each architecture predicts words.
What is the main advantage of using word embeddings?
Focus on what embeddings do with dimensionality.
True or False: GloVe uses local context to create word embeddings.
Think about how GloVe and Word2Vec differ in method.
Discuss how word embeddings could enhance a chatbot's understanding of user queries.
Consider how embeddings allow machines to grasp context and meaning.
Analyze the potential limitations of word embeddings in understanding complex phrases or idioms.
Think about how word meanings can change based on context.
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