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Deep Learning with Keras

You're reading from   Deep Learning with Keras Implementing deep learning models and neural networks with the power of Python

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781787128422
Length 318 pages
Edition 1st Edition
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Authors (2):
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Antonio Gulli Antonio Gulli
Author Profile Icon Antonio Gulli
Antonio Gulli
Sujit Pal Sujit Pal
Author Profile Icon Sujit Pal
Sujit Pal
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Table of Contents (10) Chapters Close

Preface 1. Neural Networks Foundations FREE CHAPTER 2. Keras Installation and API 3. Deep Learning with ConvNets 4. Generative Adversarial Networks and WaveNet 5. Word Embeddings 6. Recurrent Neural Network — RNN 7. Additional Deep Learning Models 8. AI Game Playing 9. Conclusion

Installing Keras on Microsoft Azure

One way to install Keras on Azure is to install the support for Docker and then get a containerized version of TensorFlow plus Keras. Online, it is also possible to find a detailed set of instructions on how to install Keras and TensorFlow with Docker, but this is essentially what we have seen already in a previous section (for more information, refer to https://blogs.msdn.microsoft.com/uk_faculty_connection/2016/09/26/tensorflow-on-docker-with-microsoft-azure/).

If you use Theano as the only backend, then Keras can run with just a click by loading a pre-built package available on Cortana Intelligence Gallery (for more information, refer to https://gallery.cortanaintelligence.com/Experiment/Theano-Keras-1).
The following sample shows how to import Theano and Keras into Azure ML directly as a ZIP file and use them in the Execute Python Script module. This example is due to...

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