| Detailinformationen |
| Quellcurriculum |
Bachelorstudium Artificial Intelligence 2021W |
| Ziele |
(*)Natural Language Processing (NLP) is the study of how to understand and process human language using computational methods. The aim of the course is to provide in depth knowledge on the essential elements of NLP, particularly based on machine learning and neural networks. Upon completing, students will be able to understand the mechanisms behind NLP systems, applied to applications such as language modeling, document classification, sentiment analysis, information retrieval, computational social science, and detection of societal biases. The students will be able to propose and weigh various solutions to NLP problems.
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| Lehrinhalte |
(*)The course covers the following topics:
- Text processing
- Sentiment analysis with machine learning
- Language modeling with neural networks
- Word embedding models (word2vec, GloVe, etc.)
- Learning compositional embeddings
- Contextualized word embeddings (practical walkthrough)
- Principles of Information Retrieval
- Footprint of societal phenomena and biases in NLP
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| Beurteilungskriterien |
(*)Written exam at the end of the semester
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| Lehrmethoden |
(*)Slide presentations with examples on blackboard.
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| Abhaltungssprache |
Englisch |
| Lehrinhalte wechselnd? |
Nein |
| Sonstige Informationen |
(*)For further information visit https://www.jku.at/en/institute-of-computational-perception/teaching/alle-lehrveranstaltungen/natural-language-processing
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| Äquivalenzen |
(*)in collaboration with 536DASCNLPU21: UE Natural Language Processing (1.5 ECTS) equivalent to
536DASCNLPK20: KV Natural Language Processing (3 ECTS)
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