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Machine learning seminar [ LINGI2379 ]


3.0 crédits ECTS  30.0 h   2q 

Teacher(s) Verleysen Michel ; Dupont Pierre (coordinator) ;
Language English
Place
of the course
Louvain-la-Neuve
Prerequisites

having passed at least one of the following courses:

  • INGI2262 Machine Learning
  • ELEC2870 Artificial neural networks
  • SINF2275 Data mining and decision making
Main themes

Themes are chosen in the domain of machine learning

Aims
  • To study in groups current issues in machine learning, pattern recognition or data analysis
  • To summarize a technical or scientific paper of the domain, convey it to colleagues, and discuss it with a critical viewpoint
Teaching methods

The course is organised as a seminar where student meet regularly to present and discuss recent scientific papers.

Les séminaires pourront être présentés en anglais ou en français par les étudiants.

Content

Illustrative examples:

  • Semi-supervised learning methods
  • Structured data mining (graphs, trees, sequences, etc.)
  • Kernel methods for classification and regression
  • Variable selection methods
  • Hidden Markov models and their applications
  • Boosting and bagging algorithms
  • Automata induction techniques
Cycle et année
d'étude
> Master [120] in Computer Science and Engineering
> Master [120] in Computer Science
Faculty or entity
in charge
> INFO


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