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Can you explain embedding in tensorflow?
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Answer / Jyoti Yadav
Embedding in TensorFlow refers to the process of converting categorical data (like words or categories) into dense vector representations that can be used in neural networks. This is often achieved using techniques like one-hot encoding, word2vec, and others.
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