FI:PV212 Seminar on ML, IR, and SV - Informace o předmětu
PV212 Seminar on Machine Learning, Information Retrieval, and Scientific Visualization
Fakulta informatikypodzim 2024
- Rozsah
- 0/2/0. 2 kr. (plus ukončení). Ukončení: k.
Vyučováno kontaktně - Vyučující
- doc. RNDr. Petr Sojka, Ph.D. (přednášející)
Mgr. Michal Štefánik (pomocník)
Mgr. Marek Kadlčík (pomocník)
Mgr. Vlastimil Martinek (pomocník) - Garance
- doc. RNDr. Petr Sojka, Ph.D.
Katedra vizuální informatiky – Fakulta informatiky
Kontaktní osoba: doc. RNDr. Petr Sojka, Ph.D.
Dodavatelské pracoviště: Katedra vizuální informatiky – Fakulta informatiky - Rozvrh
- Čt 19. 9. až Čt 12. 12. Čt 10:00–11:50 A502
- Předpoklady
- SOUHLAS
Interest in research problems in areas of Machine Learning, Scientific Visualization, Information Retrieval and Digital Typography. Courage to learn how to move the human knowledge and understanding in these areas by CS research. Willingness to study particular topic of choice, and refer, discuss and brainstorm about it with others. - Omezení zápisu do předmětu
- Předmět je nabízen i studentům mimo mateřské obory.
- Mateřské obory/plány
- předmět má 32 mateřských oborů, zobrazit
- Cíle předmětu
- The aim of the seminar is to give floor to students (both pregradual and gradual) to read, practice and present scientific results (eitheir their or those ackquires from scientific papaers. Every student will have her/his own presentation in the seminar.
- Výstupy z učení
- At the end of the course students will have experience in presenting and discussion of their or other (from readings) research. They also will be able to prepare scientific presentation of their work (slides, thesis), and communicate scientific results.
- Osnova
- Referred topics/projects for every year will be posted on the web page of the course, and negotiated with registered students. The lectures consist mostly of students' presentations. The presentations and discussion are in English. The students will have an ample space in the discussions after each presentation.
- Literatura
- WITTEN, I. H. a Eibe FRANK. Data mining : practical machine learning tools and techniques. 2nd ed. Amsterdam: Elsevier, 2005, xxxi, 525. ISBN 0120884070. 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
- KNUTH, Donald Ervin. Digital typography. Stanford: Center for the Study of Language and Information, 1999, xv, 685. ISBN 1575860112. info
- Výukové metody
- Lectures intermixed with seminar style discussions and brainstormings to solve given research problems. Students will be given readings as a preparation for the contact teaching hours, if they will not come with their own research problems.
- Metody hodnocení
- Every student will either refer about some research topic from readings or solve some project (typical from their thesis) and present its solution. Students must attend the seminar regularly and take active part in the seminar discussions.
- Vyučovací jazyk
- Angličtina
- Navazující předměty
- Informace učitele
- http://www.fi.muni.cz/~sojka/PV212/
Course is especially useful to be enrolled by students preparing their research thesis in the areas covered. "Education is not about the filling of a bucket but the lighting of a fire!" William Butler Yeats - Další komentáře
- Studijní materiály
Předmět je vyučován každý semestr.
- Statistika zápisu (nejnovější)
- Permalink: https://is.muni.cz/predmet/fi/podzim2024/PV212