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Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

You're reading from   Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide A practical guide to building neural networks using Microsoft's open source deep learning framework

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789802993
Length 208 pages
Edition 1st Edition
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Author (1):
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Willem Meints Willem Meints
Author Profile Icon Willem Meints
Willem Meints
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Table of Contents (9) Chapters Close

Preface 1. Getting Started with CNTK FREE CHAPTER 2. Building Neural Networks with CNTK 3. Getting Data into Your Neural Network 4. Validating Model Performance 5. Working with Images 6. Working with Time Series Data 7. Deploying Models to Production 8. Other Books You May Enjoy

Recurrent neural networks variations

Recurrent neural networks can be used in a variety of ways. In this section we'll take a look at the different variations of recurrent neural networks and how they can be used to solve specific types of problems. Specifically we'll look at the following variations:

  • Predicting a single output based on an input sequence
  • Predicting a sequence based on a single input value
  • Predicting sequences based on other sequences

Finally we'll also explore stacking multiple recurrent neural networks together and how that helps get better performance in a scenario like processing text.

Let's take a look at the scenarios in which recurrent networks can be used, as there are several ways in which you can use the unique properties of recurrent neural networks.

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