====== Symbolic Machine Learning (B4M36SMU and BE4M36SMU)  ======

===== Annotation =====
The course will consist of the following parts:
  * **Reinforcement learning**
  * **Learning probability distributions** with a graphical model (Bayes Networks)
  * **Natural language processing**
  * **Selected topics from computational learning theory**. 
The lectures are given in English for all students.



===== Expected Distribution of Student Effort =====

|**Hours**  |//supervised sessions//|//self-study/homework//|//total//|
|//lectures//|28|28|56|
|//tutorials//|28|28|56|
|//projects//|0|53|53|
|//total//|56|109 |**165** |

165 hours ~ 6 ECTS credits



===== Teachers =====
  * Lecturers
    * [[kuzelon2@fel.cvut.cz|Ondřej Kuželka]] (KN-E:434)
    * [[gustav.sir@cvut.cz |Gustav Šír]] (KN-E:435)
    * [[zelezny@fel.cvut.cz|Filip Železný]] (KN-E:433)
  * Course Assistants
    * [[rysavpe1@fel.cvut.cz|Petr Ryšavý]] (KN:E-435)
    * [[gustav.sir@cvut.cz |Gustav Šír]] (KN-E:435)
    * [[tothjan2@fel.cvut.cz|Jan Tóth]] (KN:E-435)