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.