GSLT: Machine Learning

The purpose of this course is to give a solid methodological foundation in machine learning for language technology, an overview of the most widely used approaches to learning, and an in-depth understanding of a subset of these approaches. The course is aimed at students with a basic knowledge of natural language processing and/or speech technology (at least the equivalent of a GSLT level 1 course in one of these areas, see NLP, Speech technology). Basic programming skills are useful as well as a rudimentary knowledge of basic statistics and probability theory.

The course consists of three parts:

The assignments for part one and two should be carried out in groups of two students. The final project may be carried out in groups of two students.

The main text book for the course is Mitchell (1997) Machine Learning, which will be used especially in the first part of the course. Students are recommended to read at least chapters 1 and 5 before the first intensive week.

NB: The official language within GSLT is English but we can decide to have lectures, seminars and discussions in Swedish instead, provided of course that all participants are comfortable with this. In any case, participants are free to formulate their contributions to discussions, whether oral or written, in any language that can be understood by the other participants (which in most circumstances means Swedish or English).



10-12, 13-15, 15-17
Introduction JN, OT
10-12, 13-15, 15-17
Generalized linear classifiers
8-10, 10-12, 13-15
Memory-based learning WD

Teachers:Joakim Nivre (JN)
Oscar Täckström (OT)
Ryan McDonald (RM)
Walter Daelemans (WD)

Study Periods

  1. The period between the first and second intensive weeks will be devoted to one assignment: Deadline: 18 October
  2. The first period after the second intensive week will be devoted to three tasks: Deadline: 22 November
  3. The second period after the second intensive week will be devoted to the course project, which is to be reported in a term paper.
    Deadline: 20 December

Closing Seminar

The closing seminar will take place at Uppsala University 14-15 January 2010.