PA164 Machine learning and natural language processing

Faculty of Informatics
Autumn 2003
Extent and Intensity
2/1. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).
Teacher(s)
Mgr. Miloslav Nepil, Ph.D. (lecturer)
doc. RNDr. Lubomír Popelínský, Ph.D. (lecturer)
Guaranteed by
prof. PhDr. Karel Pala, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 18:00–19:50 B001, Wed 10:00–11:50 X Datový projektor, Wed 10:00–11:50 B410
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 (in Czech)
Bude podán přehled učicích metod a systémů pro zpracování přirozeneého jazyka. Důraz je kladen na aplikace těchto metod. Součástí předmětu je projekt.
Syllabus
  • Natural language processing(NLP). Corpora. Tools for NLP.
  • Inroduction to machine learning
  • Disambiguation. Morphological disambiguaiton and word-sense disambiguation
  • Shallow parsing, syntactic analysis and learning
  • Entity recognition and collocations
  • Document categorization
  • Information extraction from text
  • Text ming
  • Web mining
  • Semantic web
Assessment methods (in Czech)
Součástí předmětu je projekt.
Language of instruction
Czech
Teacher's information
http://www.fi.muni.cz/~popel/lectures/ll/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2003, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2003/PA164