Introduction to Natural Language Processing

Modulnummer: Q06-12
Englischer Titel: Introduction to Natural Language Processing
Leistungspunkte: 6
Lehrperson: Akbik

Empfohlene Vorkenntnisse

- Solid knowledge of Python since all class assignments will be in Python (using NumPy and PyTorch)
- Basic machine learning and/or deep learning knowledge will be helpful

Zwingende Voraussetzungen

keine

Inhalt

Natural language processing (NLP) is the study of computational models of human language, with the ultimate goal of enabling machines to understand and use human language. Due to the presumed connection between human intelligence and human language use, NLP is a core field within artificial intelligence (AI) and currently the focus of significant scientific research, technology development and public interest. The advent of deep learning has seen progress in NLP accelerate over the past years, with numerous major scientific breakthroughs.

This class provides an introductory overview of NLP. We will introduce a range of different NLP tasks such as information extraction, document classification, sequence labeling, machine translation and question-answering, and use these tasks to discuss common challenges and solutions in NLP. This will include methods to learn word and sentence representations, as well as neural architectures for NLP. Since deep learning is now crucial to NLP, the course will include an introduction into the deep learning framework PyTorch. Students will put the covered topics into practice in weekly implementation assigments in Python.

Erforderliche Arbeitsleistungen für LP-Vergabe und Prüfungszulassung

- completion of homework assignments
- programming tasks
- active participation incl. presentations of assignments

Lehrveranstaltungen

Vorlesung: 2 SWS
Übung: 2 SWS

Zugeordneter Vertiefungsschwerpunkt

Algorithmen und Modelle: nein
Modellbasierte Systementwicklung: nein
Daten- und Wissensmanagement: ja
Ohne Vertiefungsschwerpunkt: nein

Sprache im Modul

Deutsch: nein
Englisch: ja

Angeboten für Studiengänge

M. Sc.: ja
M. Ed.: ja
Wirtschaftsmaster: ja

Angeboten im

Wintersemester: ja
Sommersemester: nein

Turnus

Jedes Jahr