Deep Learning - Recurrent Neural Networks with TensorFlow - Embeddings

The video tutorial discusses handling text data in natural language processing (NLP), focusing on the limitations of one-hot encoding due to its inefficiency and lack of meaningful geometrical structure. It introduces embedding layers as a more efficient alternative, allowing words to be represented as dense vectors with meaningful relationships. The tutorial also touches on training embeddings and the use of pre-trained vectors like Word2Vec and GloVe.

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