UnivIS
Informationssystem der Friedrich-Alexander-Universität Erlangen-Nürnberg © Config eG 

Complex Systems: Information, neurophysics, machine learning (CS4)

Dozent/in
PD Dr. Claus Metzner

Angaben
Vorlesung mit Übung
4 SWS, benoteter Schein, ECTS-Studium, ECTS-Credits: 5
nur Fachstudium, Sprache Englisch, "Lectures and exercises online. Please visit http://tinyurl.com/cm-complex-systems for further information."
Zeit und Ort: Di 16:00 - 19:00, Raum n.V.

Studienfächer / Studienrichtungen
WF Ph-BA 5 (ECTS-Credits: 5)
WF Ph-MA ab 1 (ECTS-Credits: 5)
WPF LaP-SE ab 5 (ECTS-Credits: 7,5)
WF PhM-BA ab 5 (ECTS-Credits: 5)
WF PhM-MA ab 1 (ECTS-Credits: 5)
WF ILS-MA ab 1 (ECTS-Credits: 5)
WF ILS-BA ab 5 (ECTS-Credits: 5)
WF M-BA ab 5 (ECTS-Credits: 5)
WF M-MA ab 1 (ECTS-Credits: 5)

Inhalt
Shannon information theory, information processing, central nervous system, human brain, biological neurons, neuron models, perceptrons, pattern recognition, classification, network training, associative memory, Hopfield networks, selforganizing maps, biological neural networks, machine learning approaches, Boltzmann machines, generative stochastic models, contrastive divergence learning, auto-encoders, self-organized feature detectors, deep belief networks, deep learning and physics, convolutional networks, image recognition, computer generated art.

ECTS-Informationen:
Credits: 5

Zusätzliche Informationen
Erwartete Teilnehmerzahl: 60

Verwendung in folgenden UnivIS-Modulen
Startsemester SS 2021:
Complex Systems 4: Information, neurophysics, machine learning (PW-CS4)

Institution: Lehrstuhl für Biophysik (Prof. Dr. Fabry)
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