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Instructors: Dr. rer. pol. Steffen Eger
Event type:
Integrated Course
Org-unit: Dept. 20 - Computer Science
Displayed in timetable as:
FoLT
Subject:
Crediting for:
Hours per week:
4
Language of instruction:
German
Min. | Max. participants:
- | -
Course Contents:
The lecture will be held in English.
This lecture provides an introduction into the fundamental perspectives, problems, methods, and techniques of text technology and natural language processing using the example of the Python programming language.
Key topics:
Natural language processing (NLP)
Tokenization and Segmentation
Part-of-speech tagging
Creating and using corpora
Statistical analysis
Syntactic analysis
Machine Learning
Categorization and classification
Information extraction
Introduction to Python
Structured programming
Data structures and IO
NLTK library for NLP
Usage of further libraries such as scikit-learn
The course is based on the Python programming language together with an open-source library called the Natural Language Toolkit (NLTK). NLTK allows explorative and problem-solving learning of theoretical concepts without the requirement of extensive programming knowledge.
Literature:
Steven Bird, Ewan Klein, Edward Loper: Natural Language Processing with Python, O'Reilly, 2009. ISBN: 978-0596516499. http://www.nltk.org/book/
Preconditions:
If you like to work with your own notebook, we kindly ask you to follow the installation instructions given at http://www.nltk.org/download.
Further Grading Information:
After attending this course, students are in a position to
• define the fundamental terminology of the language technology field,
• specify and explain the central questions and challenges of this field,
• explicate and implement simple Python programs,
• transfer the learned techniques and methods to practical application scenarios of text understanding, as well as
• critically assess their merits and limitations.
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