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

Fakulta informatiky
podzim 2021
Rozsah
0/2/0. 2 kr. (plus ukončení). Ukončení: k.
Vyučující
doc. RNDr. Petr Sojka, Ph.D. (přednášející)
RNDr. Vít Starý Novotný, Ph.D. (pomocník)
Mgr. Dávid Lupták (pomocník)
Mgr. Michal Štefánik (pomocník)
Mgr. Mikuláš Bankovič (pomocník)
Mgr. Vlastimil Martinek (pomocník)
Mgr. Marek Petrovič (pomocník)
Mgr. Jakub Ryšavý (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 16. 9. až Čt 9. 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 79 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 každoročně.
Předmět je zařazen také v obdobích podzim 2008, podzim 2009, podzim 2010, podzim 2011, podzim 2012, podzim 2013, podzim 2014, podzim 2015, podzim 2016, podzim 2017, podzim 2018, podzim 2019, podzim 2020, podzim 2022, jaro 2023, podzim 2023, jaro 2024, podzim 2024, jaro 2025.