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Machine Learning with TensorFlow 1.x

You're reading from   Machine Learning with TensorFlow 1.x Second generation machine learning with Google's brainchild - TensorFlow 1.x

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781786462961
Length 304 pages
Edition 1st Edition
Languages
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Authors (3):
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Saif Ahmed Saif Ahmed
Author Profile Icon Saif Ahmed
Saif Ahmed
Quan Hua Quan Hua
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Quan Hua
Shams Ul Azeem Shams Ul Azeem
Author Profile Icon Shams Ul Azeem
Shams Ul Azeem
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with TensorFlow FREE CHAPTER 2. Your First Classifier 3. The TensorFlow Toolbox 4. Cats and Dogs 5. Sequence to Sequence Models-Parlez-vous Français? 6. Finding Meaning 7. Making Money with Machine Learning 8. The Doctor Will See You Now 9. Cruise Control - Automation 10. Go Live and Go Big 11. Going Further - 21 Problems 12. Advanced Installation

Actual cats and dogs

We've demonstrated our new tools on the notMNIST dataset, which was helpful as it served to provide a comparison to our earlier simpler network setup. Now, let's progress to a more difficult problem—actual cats and dogs.

We'll utilize the CIFAR-10 dataset. There will be more than just cats and dogs, there are 10 classes—airplanes, automobiles, birds, cats, deer, dogs, frogs, horses, ships, and trucks. Unlike the notMNIST set, there are two major complexities, which are as follows:

  • There is far more heterogeneity in the photos, including background scenes
  • The photos are color

We have not worked with color datasets before. Luckily, it is not that different from the usual black and white dataset—we will just add another dimension. Recall that our previous 28x28 images were flat matrices. Now, we'll have 32x32x3 matrices...

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