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You're reading from  Deep Learning Quick Reference

Product typeBook
Published inMar 2018
Reading LevelExpert
PublisherPackt
ISBN-139781788837996
Edition1st Edition
Languages
Python
Tools
KerasTensorFlow
Concepts
Deep Learning
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Mike Bernico
Mike Bernico
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Mike Bernico

Mike Bernico is a Lead Data Scientist at State Farm Mutual Insurance Companies. He also works as an adjunct for the University of Illinois at Springfield, where he teaches Essentials of Data Science, and Advanced Neural Networks and Deep Learning. Mike earned his MSCS from the University of Illinois at Springfield. He's an advocate for open source software and the good it can bring to the world. As a lifelong learner with umpteen hobbies, Mike also enjoys cycling, travel photography, and wine making.
Read more about Mike Bernico

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Sequence-to-sequence models

The networks that we've looked at so far have done some truly amazing things. But they've all had one pretty big limitation: they can only be applied to problems where the output is of a fixed and well-known size.

Sequence-to-sequence models are able to map sequences of inputs to sequences of outputs with variable lengths.

You might also see the terms sequence-to-sequence or even Seq2Seq. These are all terms for sequence-to-sequence models.

When using a sequence-to-sequence model, we will take a sequence in and get a sequence out in exchange. These sequences don't have to be the same length. Sequence-to-sequence models allow us to learn a mapping between the input sequence and the output sequence.

There are a variety of applications where sequence-to-sequence models might be useful, and we will talk about those applications next.

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Deep Learning Quick Reference
Published in: Mar 2018Publisher: PacktISBN-13: 9781788837996
© 2018 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Mike Bernico

Mike Bernico is a Lead Data Scientist at State Farm Mutual Insurance Companies. He also works as an adjunct for the University of Illinois at Springfield, where he teaches Essentials of Data Science, and Advanced Neural Networks and Deep Learning. Mike earned his MSCS from the University of Illinois at Springfield. He's an advocate for open source software and the good it can bring to the world. As a lifelong learner with umpteen hobbies, Mike also enjoys cycling, travel photography, and wine making.
Read more about Mike Bernico

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