Organizers: Bo Bernhardsson, Kalle Åström, Magnus Fontes


Course TAs: Fredrik Bagge Carlsson, Martin Karlsson


This is a PhD course organized in the form of a reading group where the work is carried out mainly by the participants.

We will use the book Deep Learning by Bengio et al.

To this we will also look at


Collection of Deep Learning material 


Prerequisities:  You are supposed to know the material in Ch 1-5 in Bengio beforehand. If you are completly new to machine learning you might want to first follow the ML course given at the math department


Examination: For credits (7.5 ECTS) you should be resposible for one session, complete at least half of the homeworks, and do a smaller deep learning project of your choice.

 We will upload our homeworks on this git repository.




Meetings: Wednesdays 10.15-12.00 M:2112B from 21/9 onwards


From November we change meeting times to Tuesdays 13.15-15 (except guest lecture on November 9)


You should upload your homework on this git repository and fill in this google doc (you need 6 finished home works. They can overlap, and some cooperation is allowed, but state who did what). Send also a presentation about your mini project