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Deep Learning - study circle

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

  • Some DL platform(s), Tensorflow (or alternatives)
  • Data sets, especially some interesting from biology provided by Magnus Fontes
  • Video Lectures
  • DL competitions, see kaggle
  • Cloud/GPU implementations


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.



  • Meeting 1, Introduction, 15/9: Thursday Sep 15 at 13.15 in M:2112B (control dept seminar room). Slides from the meeting: BoB, Fredrik BaggeCarlsson, MagnusFontes, KalleÅström. Start reading Goodfellow part 2, pp 167-487. Install Synapse and Slack when you get invitiations. Also install a platform of your choice (e.g. Tensorflow) and run a tutorial of your choice. Watch the video by Bengio:


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