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Literature and examination

Literature

In the lecture plan (see HT 2015, Schedule and course plan in the menu to the left), we have stated the chapters and articles that should be read before each lecture.

Text Book

  • C. Bishop. Pattern Recognition and Machine Learning. Springer 2006.

The book can be ordered in paper format from your favorite internet bookstore and found using ISBN 978-0387310732. The book has a website at http://research.microsoft.com/en-us/um/people/cmbishop/PRML/index.htm.

Articles

Other Resources

There are a large number of video lectures on Machine Learning available. We recommend, e.g.,

To get an idea of state-of-the-art in Machine Learning research and development, take a look at the program of the annual conferences ICML and NIPS.

Examination

Assignments

The examination in the course is performed through:

  • Two home assignments (4.0 credits). The assignments are performed individually, and presented orally as described in the assignment descriptions. Grade: A - F(fail).
  • A project assignment (3.5 credits). The projects are performed in groups of 4-5 students, and presented with a short written report, as well as an oral presentation given by all group members. Grade (normally the same for all group members): A - F(fail).

Details about the assignments themselves can be found under Assignments and Project in the menu.

Grading

The course grade is the weighted average of the assignment grade and the project grade, according to the following:

Assignment \ Project A B C D E
A A A B B C
B B B B C C
C B C C C D
D C C D D D
E C D D E E