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What is word embedding in tensorflow ?
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Answer / Prince Gupta
Word embeddings in TensorFlow are a way to represent words as high-dimensional vectors, preserving semantic properties of the words. This is useful for natural language processing tasks. In TensorFlow, you can use pre-trained word embeddings like Word2Vec or GloVe, or train your own using techniques like CBOW (Continuous Bag of Words) and SkipGram.
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