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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


In the sections to follow, we will show how to install Keras on multiple platforms.

Step 1 — install some useful dependencies

First, we install the numpy package, which provides support for large, multidimensional arrays and matrices as well as high-level mathematical functions. Then we install scipy, a library used for scientific computation. After that, it might be appropriate to install scikit-learn, a package considered the Python Swiss army knife for machine learning. In this case, we will use it for data exploration. Optionally, it could be useful to install pillow, a library useful for image processing, and h5py, a library useful for data serialization used by Keras for model saving. A single command line is enough for installing what is needed. Alternatively, one can install Anaconda Python, which will automatically install numpy, scipy, scikit-learn, h5py, pillow, and a lot of other libraries that are needed for scientific computing (for more information, refer to...

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