Deep Learning (CAS machine intelligence)

This course in deep learning focuses on practical aspects of deep learning.

For the hands-on part we provide a docker container (details and installation instruction).

Other resources

We took inspiration (and sometimes slides / figures) from the following resources.

Deep Learning Book (DL-Book) http://www.deeplearningbook.org/. This is a quite comprehensive book which goes far beyond the scope of this course.

Convolutional Neural Networks for Visual Recognition http://cs231n.stanford.edu/, has additional material and youtube videos of the lectures. While the focus is on computer vision, it also treats other topics such as optimization, backpropagation and RNNs. Lecture notes can be found at http://cs231n.github.io/.

More TensorFlow examples can be found at dl_tutorial

Another applied course in DL: TensorFlow and Deep Learning without a PhD

Syllabus

The course is split in 8 sessions, each 4 hours long.