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TU Berlin

Inhalt des Dokuments

Lupe


General information

  • The courses Machine Intelligence I and II can be heard independently.
  • Information regarding the tutorials and the exams can be found on the ISIS page.
  • Lecture and tutorials are held in English.
  • The registration procedure is announced in the first lecture. Prior registration/reservation is not possible.



Prerequisites

  • Mathematical knowledge: analysis, linear algebra, probability calculus and statistics.
  • Basic programming skills, (preferably Python, Matlab, R or Julia).



Topics covered

  • Connectionist neurons
  • Feedforward multilayer networks
  • Recurrent neural networks
  • Learning and generalization
  • Radial Basis Functions
  • Elements of learning theory
  • Support Vector Machines
  • Uncertainty and inference
  • Bayesian networks
  • Bayesian inference and neural networks
  • Reinforcement learning



Target Audience / Assessment and Grading

Program
Form of Assessment
MSc in Computational Neuroscience
The two courses (MI I and II) form a single module (12 ECTS).

60% of all assignments & oral exam
MSc in Computer Science
Each of the two courses (MI I or II) can be taken as a separate module (6 ECTS).

60% of all assignments & written exam
Other study programs (e.g., mathematics, natural, and engineering sciences)
Each of the two courses (MI I or II) can be taken as a separate module (6 ECTS).

60% of all assignments & written exam

 

For further information please consult (lecturer, in charge) or (tutor).

Zusatzinformationen / Extras

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Auxiliary Functions

Lecture

Machine Intelligence I
0434 L 866
Lecture

Lecturer: Klaus Obermayer

Period:
from 19.10.2017

Th 12:15 - 13:45 o'clock

Location: EW 203

ISIS

Tutorials

Exercise

Lecturer: Moritz Augustin

Period:
from 26.10.2017

Th 14:15 - 17:45 o'clock

Location: MAR 0.011



ISIS