Online Course on Neural Networks

Professor: Hugo Larochelle

Welcome to my online course on neural networks! I've put this course together while teaching an in-class version of it at the Université de Sherbrooke.

This is a graduate-level course, which covers basic neural networks as well as more advanced topics, including:

  • Deep learning.
  • Conditional random fields.
  • Restricted Boltzmann machines.
  • Autoencoders.
  • Sparse coding.
  • Convolutional networks.
  • Vector word representations.
  • and many more...

In the Content section, you'll find links to video clips describing these different concepts, as well as recommended readings. The content is laid out into sections that should correspond to about one week's worth of work.

In the Evaluations section, you'll find 3 programming assignments, in Python, that I use in my class. They are good opportunities to put in practice some of the concepts covered by the course.