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Before choosing courseID2000 Machine Learning 6.0 creditsAdministrate About course

This course will give the student a good fundamental knowledge about the field of Machine Learning: the study of artifacts, in particular algorithms that improve their performance with experience. The course will discuss the character of what is learned, properties of basic algorithms, issues of representation and general problems that have to be handled independent of representation and choice of algorithms. Some special emphasize will be given to the two specific technical areas: inductive logic programming and genetic algorithms.

Course offering missing for current semester as well as for previous and coming semesters

Content and learning outcomes

Course contents

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Intended learning outcomes

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Course Disposition

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Literature and preparations

Specific prerequisites

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Recommended prerequisites

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Literature

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Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F

Examination

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Opportunity to complete the requirements via supplementary examination

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Opportunity to raise an approved grade via renewed examination

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Examiner

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Further information

Course web

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Offered by

ICT/Systems Science (SU)

Main field of study

Information Technology

Education cycle

Second cycle

Add-on studies

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