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Sequence to Sequence Modeling: Neural Machine Translation with Sockeye
Abstract:

NMT is often performed using sequence to sequence modeling, where the input is a sequence of variable length tensor representation of a sentence in source language , and the output is the another variable length tensor representation of target language. Sockeye project, a sequence-to-sequence framework for Neural Machine Translation based on Apache MXNet Incubating. It implements the well-known encoder-decoder architecture with attention. The talk covers LSTM networks, NMT fundamentals, an overview of how to use Sockeye for implementing translation tasks, and areas of active research for those who are interested in further study of the subject.

 
Topics:
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Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23496
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