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You're reading from  Deep Learning with Theano

Product typeBook
Published inJul 2017
PublisherPackt
ISBN-139781786465825
Edition1st Edition
Tools
Theano
Concepts
Deep Learning
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Author (1)
Christopher Bourez
Christopher Bourez
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Christopher Bourez

Christopher Bourez graduated from Ecole Polytechnique and Ecole Normale Suprieure de Cachan in Paris in 2005 with a Master of Science in Math, Machine Learning and Computer Vision (MVA). For 7 years, he led a company in computer vision that launched Pixee, a visual recognition application for iPhone in 2007, with the major movie theater brand, the city of Paris and the major ticket broker: with a snap of a picture, the user could get information about events, products, and access to purchase. While working on missions in computer vision with Caffe, TensorFlow or Torch, he helped other developers succeed by writing on a blog on computer science. One of his blog posts, a tutorial on the Caffe deep learning technology, has become the most successful tutorial on the web after the official Caffe website. On the initiative of Packt Publishing, the same recipes that made the success of his Caffe tutorial have been ported to write this book on Theano technology. In the meantime, a wide range of problems for Deep Learning are studied to gain more practice with Theano and its application.
Read more about Christopher Bourez

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Installing and configuring Keras

Keras is a high-level neural network API, written in Python and capable of running on top of either TensorFlow or Theano. It was developed to make implementing deep learning models as fast and easy as possible for research and development. You can install Keras easily using conda, as follows:

conda install keras

When writing your Python code, importing Keras will tell you which backend is used:

>>> import keras
Using Theano backend.
Using cuDNN version 5110 on context None
Preallocating 10867/11439 Mb (0.950000) on cuda0
Mapped name None to device cuda0: Tesla K80 (0000:83:00.0)
Mapped name dev0 to device cuda0: Tesla K80 (0000:83:00.0)
Using cuDNN version 5110 on context dev1
Preallocating 10867/11439 Mb (0.950000) on cuda1
Mapped name dev1 to device cuda1: Tesla K80 (0000:84:00.0)

If you have installed Tensorflow, it might not use Theano. To specify which backend to use, write a Keras configuration file, ~/.keras/keras.json: 

{
    "epsilon": 1e-07...
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Deep Learning with Theano
Published in: Jul 2017Publisher: PacktISBN-13: 9781786465825
© 2017 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Christopher Bourez

Christopher Bourez graduated from Ecole Polytechnique and Ecole Normale Suprieure de Cachan in Paris in 2005 with a Master of Science in Math, Machine Learning and Computer Vision (MVA). For 7 years, he led a company in computer vision that launched Pixee, a visual recognition application for iPhone in 2007, with the major movie theater brand, the city of Paris and the major ticket broker: with a snap of a picture, the user could get information about events, products, and access to purchase. While working on missions in computer vision with Caffe, TensorFlow or Torch, he helped other developers succeed by writing on a blog on computer science. One of his blog posts, a tutorial on the Caffe deep learning technology, has become the most successful tutorial on the web after the official Caffe website. On the initiative of Packt Publishing, the same recipes that made the success of his Caffe tutorial have been ported to write this book on Theano technology. In the meantime, a wide range of problems for Deep Learning are studied to gain more practice with Theano and its application.
Read more about Christopher Bourez

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