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Hands-On Deep Learning for Images with TensorFlow

You're reading from   Hands-On Deep Learning for Images with TensorFlow Build intelligent computer vision applications using TensorFlow and Keras

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Product type Paperback
Published in Jul 2018
Publisher Packt
ISBN-13 9781789538670
Length 96 pages
Edition 1st Edition
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Author (1):
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Will Ballard Will Ballard
Author Profile Icon Will Ballard
Will Ballard
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Deep neural network

Now, we're going to create an actual deep neural network using convolution.

In this section, we'll cover how to check to make sure we're running on a GPU, which is an important performance tip. Then, we'll load up our image data, and then we'll build a multiple block deep neural network, which is much deeper than anything we've created before. Finally, we'll compare the results of this deep neural network with our shallow convolutional neural network in the previous section.

Here, at the top, we're importing the necessary Python packages:

Importing packages

This is the same as we did for the standard convolutional neural network. The difference regarding making a deep neural network is that we're simply going to be using the same layers even more. In this next block, we're going directly to tensorflow and importing...

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