Palacký University Olomouc
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for academic year 2026/2027
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Course: Machine Learning a Data Mining 2

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Course title Machine Learning a Data Mining 2
Course code KMI/MLDM2
Organizational form of instruction Lecture + Exercise
Level of course Master
Year of study 2
Semester Winter
Number of ECTS credits 4
Language of instruction Czech
Status of course Compulsory, Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Bělohlávek Radim, prof. RNDr. Ph.D., DSc.
  • Outrata Jan, doc. Mgr. Ph.D.
  • Trnečka Martin, doc. RNDr. Ph.D.
  • Bartl Eduard, doc. RNDr. Ph.D.
Course content
The course is the second part of a two-semester sequence devoted to the main methods of machine learning and knowledge discovery from data. Matrix methods in data analysis; motivation and introductory examples. Review of concepts from linear algebra. QR decompositions and their applications. SVD (singular value decomposition) and its applications. Factor analysis of binary data. NMF (non-negative matrix factorization) and its applications. PCA (principal component analysis) and its applications.

Learning activities and teaching methods
Lecture, Dialogic Lecture (Discussion, Dialog, Brainstorming)
Learning outcomes
Prerequisites
unspecified

Assessment methods and criteria
unspecified
Recommended literature
  • C. Borgelt, M. Steinbrecher, R. Kruse. Graphical Models Representations for Learning, Reasoning and Data Mining.
  • Hastie, T., Tibshirani, R., Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction.
  • Christopher Bishop. Pattern Recognition and Machine Learning.
  • Ian Goodfellow and Yoshua Bengio and Aaron Courville. Deep Learning.
  • K. P. Murphy. Machine Learning: A Probabilistic Perspective.
  • Kruse, R., Borgelt, C., Braune, C., Mostaghim, S., Steinbrecher, M. Computational Intelligence.
  • Nielsen, Thomas Dyhre, VERNER JENSEN, FINN. Bayesian Networks and Decision Graphs.
  • Pang-Ning Tan Michael Steinbach Vipin Kumar. Introduction to Data Mining.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Science Study plan (Version): Bioinformatics (2021) Category: Informatics courses 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Applied Computer Science - Specialization in Software Development (2024) Category: Informatics courses 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Computer Science - Specialization in Artificial Intelligence (2020) Category: Informatics courses 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Applied Computer Science - Specialization in Computer Systems and Technologies (2024) Category: Informatics courses 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Computer Science - Specialization in General Computer Science (2020) Category: Informatics courses 2 Recommended year of study:2, Recommended semester: Winter
Palacký University Olomouc, date of update: 30.10.2026 23:53. Data created for academic year 2026/2027