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This video tutorial introduces the Embedding layer of PyTorch by explaining its functionality and common use cases. The Embedding layer is described as a simple lookup table that stores embeddings of a fixed dictionary and size. It has two positional arguments: the number of embeddings and the embeddings dimension. Embedding is essentially a two-dimensional array that represents different entities to embed, such as characters in a language model.
