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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
Languages
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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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Toc

Table of Contents (9) Chapters Close

Preface 1. Getting Started with CNTK 2. Building Neural Networks with CNTK FREE CHAPTER 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

Summary

In this chapter, we've looked at using neural networks to classify images. It's very different from working with normal data. Not only do we need a lot more training data to get the right result, we also need a different architecture to work with images that is better suited for the job.

We've seen how convolution layers and pooling layers can be used to essentially create an advanced photo filter that extracts important details from the data and summarize these details to reduce the dimensionality of the input to a manageable size.

Once we have used the advanced properties of the convolution filters and pooling filters, it's back to business as usual with dense layers to produce a classification network.

It can be quite hard to come up with a good structure for an image classification model, so it's always a good idea to check out one of the...

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