== Integrated Lecture "Kognitive Algorithmen" == 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 will alternated a lecture and a practice session. In the practice session students will implement and apply machine learning algorithms on real data in Python. === Dates === ||'''Date:''' || Thursday, 10:00 - 12:00, 17.04.2014 - 17.07.2014|| || '''Room:'''|| MAR 0.007 || || '''Responsible:''' || [[http://www.ml.tu-berlin.de/menue/members/klaus-robert_mueller/|Prof. Dr. Klaus-Robert Müller]] || || '''Contact Person:''' || [[http://www.user.tu-berlin.de/irene.winkler/| Irene Winkler]]|| === Topics === We will cover * Supervised learning (linear regression techniques, linear classification, kernel based regression) * Unsupervised Learning (Principal Component Analysis, Clustering) * Model Selection More information can be found on the [[https://www.isis.tu-berlin.de/2.0/course/view.php?id=1928 | ISIS]] Website. The password will be announced in the first lecture. === Prerequisites === The following are prerequisites are helpful for taking the course: * Basic knowledge in linear algebra and calculus * Basic programming knowledge, programming in Python As thematical preparation, it is recommended to visit '''the Python course or the mathematical foundations course''' which are also accreditable as optional compulsory course part and '''take place in the week prior to the start of the lecture period'''. === Credits === The integrated lecture is the compulsory part of the B.Sc. module "Kognitive Algorithmen" in Computer Science. This '''"Kognitive Algorihtmen" 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): a [[Main/SS14_MatheKurs|Math refresher course]], an [[Main/SS14_PythonKurs | introduction to python programming ]] or a [[Main/SS14_AKA|seminar ("Applications of Cognitive Algorithms")]] for a more in-depth treatment of selected applications. The grade will be determined in a written exam at the end of the semester. You need to solve 50% of the exercise sheets to take part in the written exam. The grades of the elective will not count towards the grade of the entire module.