July 2018
Beginner to intermediate
312 pages
8h 31m
English
Content preview from Hands-On Natural Language Processing with Python
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Neural machine translation
Neural machine translation (NMT) uses a neural network to learn to translate text from a source language into a target language. Unlike SMT, one key advantage of NMT is that it needs only one model to translate end-to-end from a source language into a target language. More importantly, NMT works on whole segments of the source text rather than chunks or phrases as in SMT. This is achieved by learning context through word embeddings. Therefore, NMT performs translation while preserving the context of the original text, as well. We will now look at some of the common deep learning architectures used in NMT.
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