• Form: 8 x 2 hour lecture
• Time: Wednesdays, 10:00-12:00.
• Dates: April 26 - June 14 2006.
  • First half, April 26 - May 17: room YZ8, Tilburg University campus.
  • Second half, May 24 - June 14: room Paviljoen J1, Eindhoven Technical University.
• Teachers:
  • dr. Antal van den Bosch, phone 013 4663117, email Antal.vdnBosch@uvt.nl
  • dr. Ton Weijters, phone 040 2473857, email a.j.m.m.weijters@tm.tue.nl

The goal of the course is to learn the basics of machine learning: the classic algorithms, and the methodologies and principles that underly the use of these algorithms. Machine learning, in essence, is a toolkit, so we will also spend time on analysing what are the right tools for the particular problems arising in process mining (an Eindhoven speciality) and natural language processing (a Tilburg speciality).

Schedule

Nr.	Date	Topic
1	26 April	Introduction: decision trees, minimal description length ppt slides | pdf handouts
2	3 May	Hyperspaces/planes/spheres, Rule learning, bias and variance ppt slides | pdf handouts
3	10 May	Memory-based learning, natural language processing, forgetting exceptions ppt slides | pdf handouts
4	17 May	Case studies in natural language processing
5	24 May	Case studies in process mining
6	31 May	Biological metaphors: neural networks
7	7 June	Biological metaphors: genetic algorithms
8	14 June	Common issues and bridges: sequence mining and processing

Literature

Correlated with the course:

• Mitchell, Tom (1997). Machine Learning. McGraw Hill.