== Integrated Lecture "Cognitive Algorithms" ==

Computer programs can learn useful cognitive skills. This integrated lecture tries to communicate an intuitive understanding of elementary concepts in machine learning and their application on real data with a special focus on methods that are simple to implement.
We recommend the [[Main/WS18_MaschinellesLernen1 | "Machine Learning 1" ]] lecture or the [[Main/SS18_MLPraktikum|"Machine learning lab course"]] for a more advanced treatment (this course is not a prerequisite). 


=== Dates ===

||'''Lecture:''' ||Thursday, 16:00-18:00 in MA 001 ||
||'''Tutorials:''' || TBD||
|| ||TBD||
|| ||TBD||
|| '''Responsible:''' || [[http://www.ml.tu-berlin.de/menue/members/klaus-robert_mueller/|Prof. Dr. Klaus-Robert Müller]] ||
|| '''Lecturer''' || Stephanie Brandl, Lorenz Vaitl ||
|| '''Contact''' || cognitivealgorithms@ml.tu-berlin.de ||

=== Lectures/Tutorials ===

Lectures and tutorials take place every other week respectively. There will be 3 groups for the tutorials, registration will happen via Moses. In the tutorials we will briefly recap the lecture and discuss the exercise sheet.

=== Assignments ===

After each lecture there will be assignments where you mainly implement the algorithms discussed in the lecture. Those assignments will be organised via ISIS.

=== Topics ===

We will cover (among other things)

 * Supervised learning (linear regression techniques, linear classification, kernel based regression, neural networks)
 * Unsupervised Learning (Principal Component Analysis, Clustering)
 * Model Selection

More information can be found on the [[https://isis.tu-berlin.de/course/view.php?id=17099|ISIS]] Website. 

=== Language ===

English

=== Prerequisites ===

The following prerequisites are helpful for taking the course:

 * Basic knowledge in linear algebra and calculus
 * Basic programming knowledge, programming in Python
 * To participate in the exam you '''first need to pass the elective course'''

=== Credits ===

The integrated lecture is the compulsory part of the B.Sc. module "Kognitive Algorithmen" in Computer Science. This "Kognitive Algorithmen" module is a 6 ECTS/SP module, and consists of 
 
 * The compulsory integrated lecture (2 SWS / 3 SP / 3 ECTS), and 
 * An elective (2 SWS / 3 SP / 3 ECTS): an [[Main/WS19_PyML| introduction to python programming ]] or a [[Main/SS19_HOT|seminar ("Hot Topics in ML")]] for a more in-depth treatment of selected applications. 

The grade will be determined in a written exam at the end of the semester. The grades of the elective will not count towards the grade of the entire module.