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Department of Mathematics and Computer Science

10907-01 Pattern Recognition Fall 2018

https://dmi.unibas.ch/de/studium/computer-science-informatik/hs18/lecture-pattern-recognition/

Lecturers Assistants

Prof. Dr. Thomas Vetter <thomas.vetter@unibas.ch> Dr. Adam Kortylewski <adam.kortylewski@unibas.ch>

Dennis Madsen <dennis.madsen@unibas.ch>

Dana Rahbani <dana.rahbani@unibas.ch>

General Information

Administrative

• You need to register at https://servi c es.unibas.ch

• Passing the final oral exam is necessary to earn credit points

• Passing the exercises is necessary to be admitted to the final exam

• You pass the exercises if you earn a minimum of 50% of the points in each exercise sheet

Exercises

• The exercises are mainly practical programming problems. You should solve them together with a partner in groups of three students. The solutions are presented orally, each student can be graded individually (15 min). We score your answer to our questions not your code. Questions are about conceptual understanding as well as results and difficulties of the code. Visiting the presentation sessions is mandatory to earn points.

• Exercises are due every two weeks. The week in-between, we will discuss the previous exercises and also answer your questions and discuss problems. Visiting the discussion sessions is not mandatory but recommended. It takes place on Monday 14 – 16, marked with “(S)” in the exercise schedule.

• The official programming language is Python.

• The 15 minutes presentation time are not to discuss syntax or run-time difficulties. Please appear fully prepared. If you experience troubles contact us early and visit the exercise discussions (marked with “(S)” in the schedule).

If you have questions or troubles feel free to ask us:

• Adam Kortylewski, adam.kortylewski@unibas.ch, office 01.001, Spiegelgasse 1

• Dennis Madsen, dennis.madsen@unibas.ch, office 01.001, Spiegelgasse 1

• Dana Rahbani, dana.rahbani@unibas.ch, office 01.001, Spiegelgasse 1

Enjoy the exercises, you will be creating your own pattern recognition machines!

Referenzen

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