Machine Learning (NIS)
Lecture #9: Bayesian Networks, EM Algorithm
Time and place:
Wednesday 11 April 2001, 14:30-16:00 in Room E3-209
Instructor:
Uffe Kjærulff
Literature:
Tom Mitchell (1997),
Machine Learning
, Ch. 6 (except 6.1-8), McGraw Hill.
Exercises:
6.1, 6.2, 6.6 + implement network in
Hugin
. What is P(PlayTennis=yes) in case of rain and strong wind?
Slides:
31 slides on 31 sheets (
PostScript
(283 KB), or
LaTeX + figures
(15 KB))
Handouts:
31 slides on 8 sheets (
PostScript
(283 KB),
PDF
(191 KB))