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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

Building your first neural network

Now that we've learned what concepts CNTK offers to build a neural network, we can start to apply these concepts to a real machine learning problem. In this section, we'll explore how to use a neural network to classify species of iris flowers.

This is not a typical task where you want to use a neural network. But, as you will soon discover, the dataset is simple enough to get a good grasp of the process of building a deep learning model. Yet it contains enough data to ensure that the model works reasonably well.

The iris dataset describes the physical properties of different varieties of iris flowers:

  • Sepal length in cm
  • Sepal width in cm
  • Petal length in cm
  • Petal width in cm
  • Class (iris setosa, iris versicolor, iris virginica)
The code for this chapter includes the iris dataset, on which you need to train the deep learning model...
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