This seminar introduces the basics of language models and neural networks for natural language processing, which continue to dominate the current research landscape in CL. We start with some basics of machine learning for language data, such as text classification and language modeling. We then look at different types of neural network architectures and how they can be applied to language modeling. We also try to reflect, evaluate, and analyze neural language models from the linguistics perspective.
Necessary prior knowledge:
- programming with Python
(Highly) recommended prior knowledge:
- basics in Computational Linguistics and/or Machine Learning
- for MA students in Linguistics, we highly recommend "Methoden der angewandten Computerlinguistik" (BA Computerlinguistik) which teaches the basics of statistical NLP
Frequency | Weekday | Time | Format / Place | Period |
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Module | Course | Requirements | |
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23-LIN-Inf Computerlinguistische Grundlagen für Informatik-Studierende | Veranstaltung aus dem Bereich computerlinguistische Grundlagen | Study requirement
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Student information |
Veranstaltung aus dem Bereich computerlinguistische Grundlagen | Study requirement
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Student information | |
Veranstaltung aus dem Bereich computerlinguistische Grundlagen | Study requirement
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Student information | |
- | Graded examination | Student information | |
23-LIN-MaCL-MethAngewCL Methoden der angewandten Computerlinguistik | Lehrveranstaltung 1 | Study requirement
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Student information |
Lehrveranstaltung 2 | Study requirement
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Student information | |
39-M-Inf-INT-adv Advanced Interaction Technology | Advanced Interaction Technology: Seminar 1 | Study requirement
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Student information |
Advanced Interaction Technology: Seminar 2 | Graded examination
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Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.