This page is currently under construction
Links to the course material will be provided in the schedule below after each class. You may want to have a look at the previous edition of the course for reference.

The course schedule

Week	Monday	Wednesday	Friday
01	Apr 19 No class	Apr 21 Introduction, organization  [slides, handout]	Apr 23 Math preliminaries  [slides, handout, notes]
02	Apr 26 Probability theory  [slides, handout, notes]	Apr 28 Probabilty theory	Apr 30 Information theory  [slides, handout, notes]
03	May 03 ML intro  [slides, handout, notes]	May 05 Classification	May 07 lab
04	May 10 Classification  [slides, handout, notes]	May 12 Classification	May 14 lab
05	May 17 ML evaluation  [slides, handout, notes]	May 19 Interim summary	May 21 lab
	May 24 semester break	May 26 semester break	May 28 semester break
06	May 31 Artificial Neural Networks  [slides, handout, notes]	Jun 02 ANNs	Jun 04 lab
07	Jun 07 Unsupervised ML  [slides, handout, notes]	Jun 09 Unsupervised ML	Jun 11 lab
08	Jun 14 Unsupervised ML	Jun 16 Dense vector representations  [slides, handout]	Jun 18 lab
09	Jun 21 Sequence learning  [slides, handout]	Jun 23 Sequence learning	Jun 25 lab
10	Jun 28 Sequential ANNs  [slides, handout]	Jun 30 Sequential ANNs	Jul 02 lab
11	Jul 05 Sequential ANNs	Jul 07 Language models  [slides]	Jul 09 lab
12	Jul 12 Language models	Jul 14 Language models / sequential RNNs	Jul 16 lab
13	Jul 19 Tokenization  [slides]	Jul 21 POS tagging and morphology  [slides]	Jul 23 lab
14	Jul 26 Summary + Text classification (?)	Jul 28 Exam discussion / preparation	Jul 30 Exam  [exam]