| Detailed information |
| Original study plan |
Bachelor's programme Artificial Intelligence 2021W |
| Objectives |
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.
|
| Subject |
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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| Criteria for evaluation |
Written exam at the end of the semester
|
| Methods |
Slide presentations with examples on blackboard.
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| Language |
English |
| Changing subject? |
No |
| Further information |
For further information visit https://www.jku.at/en/institute-of-computational-perception/teaching/alle-lehrveranstaltungen/natural-language-processing
|
| Corresponding lecture |
in collaboration with 536DASCNLPU21: UE Natural Language Processing (1.5 ECTS) equivalent to
536DASCNLPK20: KV Natural Language Processing (3 ECTS)
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