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Machine Intelligence I (supervised methods)

Lupe [1]

General information

  • The course Machine Intelligence I will be offered during WS 20/21 in an online format. However, the exam at the end of the semester is a written exam which will take place on-site. Remote online exams will not be possible.
  • The courses Machine Intelligence I and II can be heard independently. You do not have to take one in order to take the other.
  • The lecture and tutorials are held in English.
  • The course is open to TU students as well as exchange students and visiting students. Non-TU students should apply to a Neben-/Gasthörschaft [2] to gain access to the course material.
  • No formal registration is required to attend the course. The registration is only relevant for the exam.
  • The exam registration procedure is announced in the first lecture. Prior registration/reservation is not possible and not necessary.
  • Information regarding the material, tutorials and the exam can be found on the ISIS page (see panel on the right).

Topics covered

  • Connectionist neuron
  • Feed-forward neural networks
  • Learning and generalization
  • Deep Learning
  • Recurrent neural architectures
  • Radial basis function networks
  • Elements of statistical learning theory
  • Structural risk minimization
  • Support vector machines
  • Uncertainty and inference
  • Bayesian networks
  • Bayesian Inference and Neural Networks
  • Reinforcement learning


  • Solid mathematical knowledge: analysis, linear algebra, probability calculus and statistics. We emphasize this requirement because the course deals with the theoretical aspects and mathematical formulations of the learning algorithms.
  • Basic programming skills, preferably Python, R, Matlab, or Julia. The programming skills are relevant for solving the programming exercises.

Target Audience / Assessment and Grading

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

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

written exam (no assignments during the course)


For further information please consult Klaus Obermayer [3] (lecturer, in charge) or Youssef Kashef [4] (assistant).


Machine Intelligence I
0434 L 866

Lecturer: Klaus Obermayer

from 18.10.2021

Location: digital

ISIS [5]



Lecturer: Youssef Kashef

from 18.10.2021

Location: digital

e-mail query [6]

ISIS [7]
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