Natural Language Processing

What it is about

You will receive a solid introduction to modern Natural Language Processing (NLP) methods. In the end you will know central concepts, algorithms and models from tokenizing, through parsing, embeddings and NER, to modern neural approaches and you will be able to read, analyze and contextualize scientific publications in the discipline for your own projects or theses.

What you will be able to do

Reproduce essential concepts, algorithms and models of modern NLP
Understand and critically evaluate scientific publications in the field
Assess the application of NLP methods to problems in research or professional projects
Prepare for practical application in a Master Lab (design/implementation of neural architectures)

What the module consists of

VorlesungConveying theoretical concepts, algorithms and models; foundation for self-study and exam preparation

Teaching method

Vorlesungen und VorlesungsaufzeichnungenPresentation of the content; enables learning about modern concepts and methods
Selbststudium (Folien, Aufzeichnungen, Hintergrundliteratur)Deepening and review of lecture content to achieve the learning objectives

Dates

LectureNatural Language Processing (IN2361)2 groups to choose from

AFri14:00–16:00
102, Hörsaal 2, "Interims I" (5620.01.102)
15× · 16.10.–05.02.
- 16.10.
- 23.10.
- 30.10.
- 06.11.
- 13.11.
- 20.11.
- 27.11.
- 04.12.
- 11.12.
- 18.12.
- 08.01.
- 15.01.
- 22.01.
- 29.01.
- 05.02.
BWed14:15–16:00
102, Hörsaal 2, "Interims I" (5620.01.102)
15× · 14.10.–03.02.
- 14.10.
- 21.10.
- 28.10.
- 04.11.
- 11.11.
- 18.11.
- 25.11.
- 02.12.
- 09.12.
- 16.12.
- 23.12.
- 13.01.
- 20.01.
- 27.01.
- 03.02.

From the current semester, not binding. You attend one of several groups; the timetable automatically suggests the one with the fewest clashes.

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