Grundlagen Intelligenter Systeme

Organization

  • Lecture: Thursday 09:50-11:30, Room S105/23 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 S202/D017

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 16 and the first meeting of the practice class/project course is scheduled for October 20, 2014.

Exam

  • Date/Time: (to be announced)
  • Room: (to be announced)

Teaching Staff

Please contact Christian M. Meyer or Nils Reimers for any organizational issues.

Course Content

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.

Key aspects:

  • Natural language processing (NLP)

    • Tokenizing
    • Segmentation
    • Part-of-Speech Tagging
    • Corpora
    • 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.

Literature

Steven Bird, Ewan Klein, Edward Loper: Natural Language Processing with Python, O'Reilly, 2009. ISBN: 978-0596516499. [Online-Version]

Expectations

What you can expect from us:

  • interactive lecture with integrated tutorials
  • problem-based and explorative learning
  • stimulating environment

What we expect from you:

  • commitment
  • feedback
  • active participation

If you like to have a jump start on NLTK, have a look at this video.

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