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# Course information T-61.5040

### Course Contents and Prerequisites

### Language Issues

**The course will be lectured in English if there are non-finnish speakers
in the audience. All course material will be in English, but the language
spoken in the exercise sessions will be decided in the first session (19.1.)**
### Announcements

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The course does *not* introduce lots of practical learning methods
to be used as black-box methods. Theories of learning are not taught
in detail either. Instead, the possibility of learning from data
without any assumptions is examined. This is shown to be impossible
from a certain point of view. Some difficulties of "weak" assumptions
are also demonstrated. Next, Bayesian methods are developed as a
well-justified approach to learning from data. Rest of the course
deals with Bayesian methods with the emphasis on ideas and not
on complicated details. One lecture will briefly examine Statistical
Learning Theory, which appears to suggest that learning from data
without assumptions is possible. This result is examined using
Bayesian approach, which reveals that the theory
actually does not support learning without assumptions.

As prerequisite information you will need the basic mathematics and probability courses, and know the basics of calculating with matrices. It is very useful to have taken some course which deals with modeling data nonlinearly (for example neural networks or pattern recognition).

Watch the webpage and the newsgroup opinnot.tik.informaatiotekniikka

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