PV212 Readings in Digital Typography, Scientific Visualization, Information Retrieval and Machine Learning

Faculty of Informatics
Autumn 2009
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing – Faculty of Informatics
Contact Person: doc. RNDr. Petr Sojka, Ph.D.
Timetable
Tue 12:00–13:50 C522
Prerequisites
SOUHLAS
Deep interest in areas of Digital Typography, Scientific Visualization, Information Retrieval and Machine Learning.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
At the end of the course students should be able to read, understand, explain and evaluate [English] scientific papers, based on experience of practising these skills in this seminar.
Syllabus
  • Topics and projects for every year will be posted on the web page of the course. On seminars students will refer about topics studied and they will be discussed thoroughly.
Literature
  • WITTEN, I. H. and Eibe FRANK. Data mining : practical machine learning tools and techniques. 2nd ed. Amsterdam: Elsevier, 2005, xxxi, 525. ISBN 0120884070. info
  • KNUTH, Donald Ervin. Digital typography. Stanford: Center for the Study of Language and Information, 1999, xv, 685. ISBN 1575860112. info
  • MITCHELL, Tom M. Machine learning. Boston: McGraw-Hill, 1997, xv, 414. ISBN 0070428077. info
  • Information retrieval :data structures & algorithms. Edited by William B. Frakes - Ricardo Baeza-Yates. Upper Saddle River: Prentice Hall, 1992, viii, 504. ISBN 0-13-463837-9. info
Teaching methods
Lectures intermixed with seminar style discussions and brainstormings to solve given topics-projects. Students will be given readings as a preparation for the contact teaching hours.
Assessment methods
Every student will either refer about some research topic or solve small research project and present its solution.
Language of instruction
English
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Teacher's information
http://www.fi.muni.cz/~sojka/PV212/
The course is also listed under the following terms Autumn 2008, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.
  • Enrolment Statistics (Autumn 2009, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2009/PV212