Deep Learning with Theano: Perform large-scale numerical and scientific computations efficiently

This book covers a complete overview of Deep Learning with Theano, a Python-based library that makes optimizing numerical expressions easy.Practical code examples address supervised, unsupervised, generative and reinforcement learning for image recognition, natural language processing, or game strategy, with best performing nets and principles.

Christopher Bourez graduated from Ecole Polytechnique and Ecole Normale Supérieure 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.