392197 Deep Learning for Natural Language Processing (PjS) (SoSe 2023)
Contents, comment
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This seminars involves the creation of effective systems for the processing of text by means of statistical methods. There will be significant challenge in integrating these components into a scalable system that can handle the large amount of data required to obtain high accuracy. In addition to the technical challenges in this course, the students will be required to read recent research papers related to the task and integrate these results into their solutions.
Teaching staff
Dates ( Calendar view )
| Frequency | Weekday | Time | Format / Place | Period | |
|---|---|---|---|---|---|
| weekly | Do | 12-14 | D2-136 | 03.04.-14.07.2023
not on: 5/18/23 / 6/8/23 / 6/15/23 |
|
| weekly | Fr | 12-14 | C01-249 | 12.05.-14.07.2023
not on: 5/19/23 |
Übungen |
Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 39-Inf-SNLP Statistical Natural Language Processing | (Project-) Seminar Statistical Natural Language Processing | - | Student information |
| - | Ungraded examination Graded examination | Student information | |
| 39-M-Inf-TMKD Text Mining and Knowledge Discovery | (Project-) Seminar Text Mining and Knowledge Discovery | Ungraded examination
Graded examination |
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.
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- Last update basic details/teaching staff:
- Wednesday, April 5, 2023
- Last update times:
- Friday, May 5, 2023
- Last update rooms:
- Friday, May 5, 2023
- Type(s) / SWS (hours per week per semester)
- project seminar (PjS) / 2
- Department
- Faculty of Technology
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