Grundlagen Intelligenter Systeme
- Lecture: Thursday 09:50-11:30, Room S202/C205
- Practice class: Monday 11:40-13:20, Room S202/C120
- Project course (TUCaN-ID 20-00-0611-pr): Monday 15:20-17:00, Room S103/110
The learning material is available from the Moodle eLeaning platform.
The required passcode will be distributed during the lecture.
The first lecture will be on October 15 and the first meeting of the practice class/project course is scheduled for October 19, 2015.
- Date/Time: February 18, 2016, 10:00 – 12:00
- Room: S202/C205
- Prof. Dr. Iryna Gurevych
- Dr. Judith Eckle-Kohler (no fixed office hour, please just ask for an appointment per mail)
- Dr. Nicolai Erbs (no fixed office hour, please just ask for an appointment per mail)
- Daniil Sorokin (no fixed office hour, please just ask for an appointment per mail)
Please contact Nicolai Erbs or Daniil Sorokin for any organizational issues.
The lecture offers an introduction into the perspectives, problems, methods and techniques of text technology. All examples and tutorials are based on the programming language Python.
- Natural language processing (NLP)
- Part-of-Speech Tagging
- Statistical analysis
- Machine Learning
- Categorization and classification
- Information Extraction
- Introduction to Python
- Data Structures
- Library NLTK
- Structured Programming
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.
The course assumes familiarity with basic computing concepts, but will not assume any knowledge of the Python language, which will be acquired during the course. 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.
Steven Bird, Ewan Klein, Edward Loper: Natural Language Processing with Python, O'Reilly, 2009. ISBN: 978-0596516499. [Online-Version]
What you can expect from us:
- interactive lecture with integrated tutorials
- problem-based and explorative learning
- stimulating environment
What we expect from you:
- active participation
If you like to have a jump start on NLTK, have a look at this video.