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Deep Learning with Theano

You're reading from  Deep Learning with Theano

Product type Book
Published in Jul 2017
Publisher Packt
ISBN-13 9781786465825
Pages 300 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Christopher Bourez Christopher Bourez
Profile icon Christopher Bourez
LinkedIn
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.
See other products by Christopher Bourez

Table of Contents (22) Chapters

Deep Learning with Theano
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Theano Basics 2. Classifying Handwritten Digits with a Feedforward Network 3. Encoding Word into Vector 4. Generating Text with a Recurrent Neural Net 5. Analyzing Sentiment with a Bidirectional LSTM 6. Locating with Spatial Transformer Networks 7. Classifying Images with Residual Networks 8. Translating and Explaining with Encoding – decoding Networks 9. Selecting Relevant Inputs or Memories with the Mechanism of Attention 10. Predicting Times Sequences with Advanced RNN 11. Learning from the Environment with Reinforcement 12. Learning Features with Unsupervised Generative Networks 13. Extending Deep Learning with Theano Index

Chapter 13. Extending Deep Learning with Theano

This chapter gives clues to go further with both Theano and Deep Learning. First, it presents how to create new operators for the Theano computation graph in Python or C, either for the CPU or the GPU. Then, interactions with other Deep Learning frameworks are studied with the support of code repositories and libraries that enable back-and-forth conversion with other technologies.

Lastly, to complete the possibilities offered by the field of Deep Learning with Theano, we develop the concepts of a new General Artificial Intelligence field.

The topics covered in this chapter are as follows:

  • Writing new operators for Theano computation graphs

  • Python code for CPU and GPU

  • The C API for CPU and GPU

  • Sharing models with other Deep Learning frameworks

  • Cloud GPUs

  • Meta learning, gradual learning, and guided learning

  • General Artificial Intelligence

This chapter gives a complete overview of Deep Learning with Theano.

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Authors (1)

Profile icon Christopher Bourez
LinkedIn
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
See other products by Christopher Bourez

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