| Uitgebreide vaknaam |
Language Technology Project |
| Leerdoelen |
After completing this course, students are able to tackle a challenge in Natural Language Processing, implement a solution, and critically assess their solution in the light of recent research papers in Natural Language Processing. |
| Omschrijving |
In this project-based course, students are going to work on a natural language processing challenge. A challenge is a practical task in NLP related to a particular research topic. The task usually comes with data-sets for training, as well as a precise evaluation metric. The intention is that students familiarize themselves with a selected research topic, implement a solution and present the outcome critically in a term paper. The course is a mix of lectures, exercises and project-based work. The focus of this class is on deep learning for NLP. |
| Uren per week |
2 |
| Onderwijsvorm |
werkcollege
|
| Toetsvorm |
presentatie, werkstuk(ken)
|
| Vaksoort |
master
|
| Docent(en) |
dr. B. Plank
|
| Verplichte literatuur |
| Titel |
Auteur |
ISBN |
Prijs |
| A Primer on Neural Network Models for Natural Language Processing (available on arXiv) |
Yoav Goldberg |
|
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| selected research articles |
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| Entreevoorwaarden |
BA exam Information Science or Artificial Intelligence or similar undergraduate programme.
Maturity in computational linguistics, meaning familiarity with basic concepts of computational linguistics and machine learning, but there will be time to review occasionally unfamiliar concepts as well. |
| Opmerkingen |
(60% term paper - 40% presentation)
Progress is open van 20 november 2017 tot en met 26 januari 2018. De (eventuele) werkgroep intekening in Nestor is open van 11 december 07.00 uur t/m 26 januari 23.59 uur. De faculteit behoudt zich het recht voor wijzigingen aan te brengen in het vakaanbod, het aantal groepen en de roostering. |
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