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Explain the concept of embeddings and their use in NLP.
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Answer / Nikhil Gupta
Embeddings are low-dimensional representations of text data in NLP. They capture the semantic meanings of words and phrases, enabling machines to understand and process natural language more effectively. Embeddings can be learned using techniques like word2vec, GloVe, or FastText.
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