Lecturers

Slides

Introduction to neural networks – Lars Kai Hansen
Markov Random Fields and Restricted Boltzmann Machines – Christian Igel
Unsupervised feature learning – Hugo Larochelle
Modern deep architectures – Aaron Courville
Dan Claudiu Cireșan – Convolutional neural networks
Deep learning in breast cancer screening – Michiel Kallenberg
Deep learning lessons from image, text and bioinformatics applications – Ole Winther

Practical sessions

Restricted Boltzmann Machines in Shark [UPDATE 15/08] Installation instructions (pdf) [UPDATE 15/08] Code Shark RBM (zip)
Autoencoders for unsupervised pre-training Installation instructions (pdf) Linux/Mac: Windows:
Convolutional neural networks for digit recognition Linux/Mac: Windows:

Suggested reading

Introduction to neural networks
Markov Random Fields and Restricted Boltzmann Machines
Unsupervised feature learning
Modern deep architectures
Convolutional neural networks

Further reading