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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
Author Profile Icon Quan Hua
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

A quick preview

Without even having TensorFlow installed, you can play with a reference implementation of TensorBoard. You can get started here:

https://www.tensorflow.org/tensorboard/index.html#graphs.

You can follow along with the code here:

https://github.com/tensorflow/tensorflow/blob/master/tensorflow/model
s/image/cifar10/cifar10_train.py
.

The example uses the CIFAR-10 image set. The CIFAR-10 dataset consists of 60,000 images in 10 classes compiled by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton. The dataset has become one of several standard learning tools and benchmarks for machine learning efforts.

Let's start with the Graph Explorer. We can immediately see a convolutional network being used. This is not surprising as we're trying to classify images here:

This is just one possible view of the graph. You can try the Graph Explorer as well. It allows deep...

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