SDA SE Wiki

Software Engineering for Smart Data Analytics & Smart Data Analytics for Software Engineering

User Tools

Site Tools


Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Last revision Both sides next revision
teaching:lectures:kga:2016:exercises [2017/11/16 11:12]
Asja Fischer
teaching:lectures:kga:2016:exercises [2018/05/09 01:59]
127.0.0.1 external edit
Line 1: Line 1:
 +~~NOTOC~~
  
 +{{page>​header&​nofooter}}
 +
 +====== KGA Exercises ======
 +
 +Exercises will take place at A207 (Römerstraße 164). \\
 +They are the best preparation for the exam.  ​
 +
 +
 +|08.11.16| 01. RDF Databases |{{:​teaching:​lectures:​kga:​2016:​01-triplestores-exercises.pdf|}} | |
 +|15.11.16| 02. Proper Graph Databases ​ | {{:​teaching:​lectures:​kga:​2016:​02-propertygraphdatabases-exercises.pdf|}} |      |      ​
 +|22.11.16| 03. Statistical Relational Learning |{{:​teaching:​lectures:​kga:​2016:​03-srl-exercises.pdf|}} ​ | | 
 +|29.11.16| 04. Tensors and Tensor Factorisation Techniques |{{:​teaching:​lectures:​kga:​2016:​04-tensors-exercises.pdf|}}| |
 +|06.12.16| 05. Alternating Least Squares|{{:​teaching:​lectures:​kga:​2016:​05-sgd-als-exercises.pdf|}} | |
 +|13.12.16| - | | | 
 +|20.12.16| 06. Neural Networks| {{:​teaching:​lectures:​kga:​2016:​06-nn-exercises.pdf|}} ​  | |
 +|10.01.17| 07. Neural Networks for KGA |{{:​teaching:​lectures:​kga:​2016:​07-nnforkga-exercises.pdf|}} | |
 +|24.01.17| 08. Latent Distance and Graph Feature Models|{{:​teaching:​lectures:​kga:​2016:​08-ldmandgfm-exercises.pdf|}}| |
 +|31.01.17| 09. Markov Logic Networks ​ | {{:​teaching:​lectures:​kga:​2016:​09-mln-exercises.pdf|}} | | 
 +|07.02.17| 11. Training SRL model |{{:​teaching:​lectures:​kga:​2016:​10-trainingsrlmodels-exercise.pdf|}} | |
 +
 +
 +
 +
 +
 + 
teaching/lectures/kga/2016/exercises.txt · Last modified: 2018/11/01 17:54 by Hamed Shariat Yazdi

SEWiki, © 2019