Courses in Stud.IP

current semester
link to course in Stud.IP Studip_icon
Machine Learning and Data Mining (VL)
Subtitle:
This course is part of the module: Machine Learning and Data Mining
Semester:
SoSe 24
Course type:
Lecture
Course number:
lv340_s24
Lecturer:
Dipl. Informatiker Rainer Marrone
Description:
  • Decision trees
  • First-order inductive learning
  • Incremental learning: Version spaces
  • Uncertainty
  • Bayesian networks
  • Learning parameters of Bayesian networks
    BME, MAP, ML, EM algorithm
  • Learning structures of Bayesian networks
  • Gaussian Mixture Models
  • kNN classifier, neural network classifier, support vector machine (SVM) classifier
  • Clustering
    Distance measures, k-means clustering, nearest neighbor clustering
  • Kernel Density Estimation
  • Ensemble Learning
  • Reinforcement Learning
  • Computational Learning Theory
Performance accreditation:
620 - Machine Learning and Data Mining<ul><li>620 - Machine Learning and Data Mining: Klausur schriftlich</li></ul>
ECTS credit points:
6
Stud.IP informationen about this course:
Home institute: Institut für Softwaresysteme (E-16)
Registered participants in Stud.IP: 160
former semester
link to course in Stud.IP Studip_icon
Machine Learning and Data Mining (VL)
Subtitle:
This course is part of the module: Machine Learning and Data Mining
Semester:
SoSe 24
Course type:
Lecture
Course number:
lv340_s24
Lecturer:
Dipl. Informatiker Rainer Marrone
Description:
  • Decision trees
  • First-order inductive learning
  • Incremental learning: Version spaces
  • Uncertainty
  • Bayesian networks
  • Learning parameters of Bayesian networks
    BME, MAP, ML, EM algorithm
  • Learning structures of Bayesian networks
  • Gaussian Mixture Models
  • kNN classifier, neural network classifier, support vector machine (SVM) classifier
  • Clustering
    Distance measures, k-means clustering, nearest neighbor clustering
  • Kernel Density Estimation
  • Ensemble Learning
  • Reinforcement Learning
  • Computational Learning Theory
Performance accreditation:
620 - Machine Learning and Data Mining<ul><li>620 - Machine Learning and Data Mining: Klausur schriftlich</li></ul>
ECTS credit points:
6
Stud.IP informationen about this course:
Home institute: Institut für Softwaresysteme (E-16)
Registered participants in Stud.IP: 160

Courses

For information on courses and modules, please refer to the current course catalogue and module manual of your degree programme.

Module / Course Period ECTS Credit Points
Module: Electrical Power Systems I: Introduction to Electrical Power Systems WiSe 6
Module: Electrical Power Systems II: Operation and Information Systems of Electrical Power Grids WiSe 6
Module: Electrical Power Systems III: Dynamics and Stability of Electrical Power Systems SuSe 6
Module: Electrical Engineering II: Alternating Current Networks and Basic Devices SuSe 6
Module: Electrical Engineering Project Laboratory SuSe 6
Module: Process Measurement Engineering SuSe 4
Module: Smart Grid Technologies WiSe, SuSe 6

Course: Seminar on Electromagnetic Compatibility and Electrical Power Systems

Further Information

WiSe, SuSe 2

SuSe: Summer Semester
WiSe: Winter Semester