Book Image

Deep Learning with Theano

By : Christopher Bourez
Book Image

Deep Learning with Theano

By: Christopher Bourez

Overview of this book

This book offers a complete overview of Deep Learning with Theano, a Python-based library that makes optimizing numerical expressions and deep learning models easy on CPU or GPU. The book provides some practical code examples that help the beginner understand how easy it is to build complex neural networks, while more experimented data scientists will appreciate the reach of the book, addressing supervised and unsupervised learning, generative models, reinforcement learning in the fields of image recognition, natural language processing, or game strategy. The book also discusses image recognition tasks that range from simple digit recognition, image classification, object localization, image segmentation, to image captioning. Natural language processing examples include text generation, chatbots, machine translation, and question answering. The last example deals with generating random data that looks real and solving games such as in the Open-AI gym. At the end, this book sums up the best -performing nets for each task. While early research results were based on deep stacks of neural layers, in particular, convolutional layers, the book presents the principles that improved the efficiency of these architectures, in order to help the reader build new custom nets.
Table of Contents (22 chapters)
Deep Learning with Theano
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Index

Further reading


You can further refer to these sources for more information:

  • Spatial Transformer Networks, Max Jaderberg, Karen Simonyan, Andrew Zisserman, Koray Kavukcuoglu, Jun 2015

  • Recurrent Spatial Transformer Networks, Søren Kaae Sønderby, Casper Kaae Sønderby, Lars Maaløe, Ole Winther, Sept 2015

  • Original code: https://github.com/skaae/recurrent-spatial-transformer-code

  • Google Street View Character Recognition, Jiyue Wang, Peng Hui How

  • Reading Text in the Wild with Convolutional Neural Networks, Max Jaderberg, Karen Simonyan, Andrea Vedaldi, Andrew Zisserman, 2014

  • Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks, Ian J. Goodfellow, Yaroslav Bulatov, Julian Ibarz, Sacha Arnoud, Vinay Shet, 2013

  • Recognizing Characters From Google Street View Images, Guan Wang, Jingrui Zhang

  • Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition, Max Jaderberg, Karen Simonyan, Andrea Vedaldi, Andrew Zisserman, 2014

  • R-CNN minus R, Karel Lenc...