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Deep Learning For Dummies
book

Deep Learning For Dummies

by John Paul Mueller, Luca Massaron
May 2019
Intermediate to advanced content levelIntermediate to advanced
368 pages
9h 55m
English
For Dummies
Content preview from Deep Learning For Dummies

Chapter 11

Introducing Recurrent Neural Networks

IN THIS CHAPTER

Bullet Understanding the importance of learning data in sequence

Bullet Creating image captions and translating languages using deep learning

Bullet Discovering the long short-term memory (LSTM) technology

Bullet Knowing about possible alternatives to LSTM

This chapter explores how deep learning can deal with information that flows. Reality is not simply changeable, but is changeable in a progressive way that is made predictable by observing the past. If a picture is a static snapshot of a moment in time, a video, consisting of a sequence of related images, is flowing information, and a film can tell you much more than a single photo or a series of photos can. Likewise for short and long textual data (from tweets to entire documents or books) and for all numeric series that represent something occurring along a timeline (for instance, a series the about sales of a product or the quality of the air by day in a city).

This chapter explains a series of new layers, the recurrent networks, and all their improvements, such as the LSTM and GRU layers. ...

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Publisher Resources

ISBN: 9781119543046Purchase book