Machine learning seminar [ LINGI2379 ]
3.0 crédits ECTS
30.0 h
2q
Teacher(s) |
Verleysen Michel ;
Dupont Pierre (coordinator) ;
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Language |
English
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Place of the course |
Louvain-la-Neuve
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Prerequisites |
having passed at least one of the following courses:
- INGI2262 Machine Learning
- ELEC2870 Artificial neural networks
- SINF2275 Data mining and decision making
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Main themes |
Themes are chosen in the domain of machine learning
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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
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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.
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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
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Cycle et année d'étude |
> Master [120] in Computer Science
> Master [120] in Computer Science and Engineering
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Faculty or entity in charge |
> INFO
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