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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

Improving model performance with data augmentation

Neural networks used for image recognition not only are difficult to set up and train, they also require a lot of data to train. Also, they tend to overfit on the images used during training. For example, when you only use photos of faces in an upright position, your model will have a hard time recognizing faces that are rotated in another direction.

To help overcome problems with rotation and shifts in certain directions, you can use image augmentation. CNTK supports specific transforms when creating a minibatch source for images.

We've included an additional notebook for this chapter that demonstrates how to use the transformations. You can find the sample code for this section in the Recognizing hand-written digits with augmented data.ipynb file in the samples for this chapter.

There are several transformations that you...

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