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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2023/2024

Mathematical methods for data analysis

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Code Completion Credits Range Language
11MMOA Z,ZK 4 2P+2C+12B Czech
Garant předmětu:
Ivan Nagy, Pavla Pecherková, Evženie Uglickich
Lecturer:
Pavla Pecherková, Evženie Uglickich
Tutor:
Pavla Pecherková, Evženie Uglickich
Supervisor:
Department of Applied Mathematics
Synopsis:

Stocastic modelling, estimation, prediction, filtration, control, methods of data analysis - k-means, DBSCAN, naive Bayes, decision trees, support vector machine.

Requirements:

probability, classical statistics, basics of algebra and calculus

Syllabus of lectures:
Syllabus of tutorials:
Study Objective:

To teach students the basic of dynamic statistic, i. e. analysis of data evolving in time. The accent is given to methods of clustering ans classification. Theoretical exposision of the subject is closely bound with a practical realization of the tasks in computer.

Study materials:

William M. Bolstad: Introduction to Bayesian Statistics, 2nd Edition. Willey, ISBN-13: 978-0470141151

P.Tan, M.Steinbach, V.Kumar: Introduction to Data Mining. Pearson Education, Inc., 2006. ISBN 0-321-32136-7

materiály na webu: http://staff.utia.cas.cz/suzdaleva/

Note:
Time-table for winter semester 2023/2024:
Time-table is not available yet
Time-table for summer semester 2023/2024:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2024-05-18
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