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Lecturer(s)
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Outrata Jan, doc. Mgr. Ph.D.
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Course content
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The course repeats the basics of data mining and machine learning, basic data preprocessing methods, classification algorithms, association analysis and clustering and introduce selected newer methods and algorithms. The course extends the introductory parts of the master's studies. Types, quality and data preprocessing, methods of reducing data dimensionality, similarity and dissimilarity of objects. Problem classification, decision trees and other methods. Bayesian networks and graph data models. Ensemble methods (bagging, boosting, random forests), performance evaluation. Association analysis, Apriori algorithm and others. Cluster theory and algorithms, cluster quality. Outliers detection methods. Reinforcement learning. Deep learning.
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Learning activities and teaching methods
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unspecified
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Learning outcomes
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Students will expand their knowledge of basic methods of machine learning and data mining and learn the newer and more advanced methods.
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Prerequisites
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unspecified
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Assessment methods and criteria
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unspecified
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Recommended literature
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Deisenroth M. P. (2020). Mathematics for Machine Learning.
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Goodfellow I., Bengio Y., Courville A. (2016). Deep learning.
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Han J., Pei J., Tong H. (2022). Data Mining: Concepts and Techniques.
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Murphy K. P. (2022). Probabilistic Machine Learning: An Introduction.
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Poole D. L., Mackworth A. K. (2023). Artificial Intelligence: Foundations of Computational Agents (3rd edition).
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Qi Yan W. (2021). Computational methods for deep learning: theoretic, practice and applications.
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Rokach L., Maimon O. (2015). Data mining with decision trees: theory and applications.
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Simovici D. A., Djeraba Ch. (2008). Mathematical Tools for Data Mining: set theory, partial orders, combinatorics.
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Sutton R. S., Barto A. G. (2018). Reinforcement Learning: An Introduction (2nd Edition).
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Tan P.-N., Steinbach M., Kumar V. (2018). Introduction to Data Mining (2nd edition).
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Witten I. H., Frank E., Hall M. A., Pal Ch. J., Foulds J. (2025). Data Mining: Practical Machine Learning Tools and Techniques.
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Zaki M. J., Meira W. Jr. (2020). Data Mining and Analysis: Fundamental Concepts and Algorithms (2nd Edition).
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