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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 course is open to TU students as well as exchange students and visiting students.
  • There is no formal prior registration required to attend the course. The registration is only relevant for the exam.
  • The registration procedure for the exam 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).

written exam (no assignments during the course)
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).

written exam (no assignments during the course)

 

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

Zusatzinformationen / Extras

Quick Access:

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Auxiliary Functions

Lecture

Machine Intelligence I
0434 L 866
Lecture

Lecturer: Klaus Obermayer

Period:
from 18.10.2018

Th 12:15 - 13:45 o'clock

Location: MA 004

ISIS

Tutorials

Exercise

Lecturer: Youssef Kashef

Period:
from 25.10.2018

Location: MAR 4.064 / MA 004



ISIS