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Vorlesungsverzeichnis >> Technische Fakultät (TF) >>
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Introduction to Machine Learning Exercises (IntroML-Ex)- Verantwortliche
- Mathias Seuret, M. Sc., Nora Gourmelon, M. Sc., Mareike Thies, M. Sc.
- Angaben
- Übung
Online
2 SWS, Schein, ECTS-Studium, ECTS-Credits: 1,25, Sprache Englisch
- Studienfächer / Studienrichtungen
- WPF ME-BA-MG6 3-5
WPF MT-BA 5
WPF INF-BA-V-ME ab 5
WPF INF-BA-V-MI ab 5
WF CE-BA-TW ab 5
WPF IuK-BA ab 5
WPF ME-MA-MG6 1-3
WPF DS-BA ab 3
- ECTS-Informationen:
- Credits: 1,25
- Contents
- This course extension is for deepening your knowledge and creating a good basis for lectures in the field of Pattern Recognition. There will be several practical programming tasks, based on the lecture content, which have to be implemented by your own. Passing this course is mandatory to pass the entire module "Introduction to Pattern Recognition". Each programming task is described in detail via stand-alone worksheets being uploaded to StudOn. You have a certain period of time to complete a worksheet and deliver the code by uploading your results to StudOn. You can use the weekly programming exercise slots to ask questions about solving the problems, but all in all, you have to do the work on your own. Of course, it is not allowed to just copy and paste from the web, which will lead to failing the course. Important: In order to successfully complete this course, you have to achieve 50% of the points in EVERY programming task! Teamwork (teams of max. 2 students) is allowed. Of course you can also work on your own.
- Literature
- lecture notes
H. Niemann: Klassifikation von Mustern H. Niemann: Pattern Analysis and Understanding S. Theodoridis and K. Koutroumbas: Pattern Recognition, 4th ed., Academic Press, 2009.
- Zusätzliche Informationen
- Schlagwörter: Mustererkennung, Vorverarbeitung, Merkmalsextraktion, Klassifkation
Erwartete Teilnehmerzahl: 250, Maximale Teilnehmerzahl: 250
- Zugeordnet zu: Introduction to Machine Learning
- Verwendung in folgenden UnivIS-Modulen
- Startsemester WS 2021/2022:
- Daten analysieren und verstehen in den Digital Humanities (DH Analyse)
- Introduction to Machine Learning (IntroML)
- Institution: Lehrstuhl für Informatik 5 (Mustererkennung)
Kurse
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