460-4099/02 – Data Analysis III (MAD III)

Gurantor departmentDepartment of Computer ScienceCredits4
Subject guarantordoc. Ing. Jan Platoš, Ph.D.Subject version guarantordoc. Ing. Jan Platoš, Ph.D.
Study levelundergraduate or graduateRequirementChoice-compulsory
Year2Semesterwinter
Study languageEnglish
Year of introduction2015/2016Year of cancellation
Intended for the facultiesUSP, FEIIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
PLA06 doc. Ing. Jan Platoš, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Graded credit 2+2
Combined Graded credit 10+0

Subject aims expressed by acquired skills and competences

The goal of this course is to deepen and improve the knowledge about data analysis methods acquired in the previous courses. The main information delivered to the students is advanced algorithms for data classification, stream data processing, advanced data structures and machine learning techniques. The students will be able to use these methods, to interpret achieved results. Moreover, the student will be able to presents and visualize the results using proper methods.

Teaching methods

Lectures
Tutorials

Summary

This course is focused on algorithms for data analysis and data visualization. The first part of the course is focused on explorative analysis and data clustering. The second part is focused on the data classification. he course describes a less complex linear methods to the more complex method based on the SVM. More advanced methods will be descibed in the last part of the course.

Compulsory literature:

1. Ian H. Witten, Eibe Frank, Mark A. Hall, Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, Morgan Kaufmann, 2011, ISBN: 978-0123748560

Recommended literature:

1. Mohammed J. Zaki, Wagner Meira, Jr., Data Mining and Analysis: Fundamental Concepts and Algorithms, Cambridge University Press, May 2014. ISBN: 9780521766333. 2. Jure Leskovec, Anand Rajaraman, David Ullman, Mining of Massive Datasets, 2nd editions, Cambridge University Press, Novemeber 2014, ISBN: 9781107077232, On-line http://infolab.stanford.edu/~ullman/mmds/book.pdf [2014-09-12]

Way of continuous check of knowledge in the course of semester

Students' knowledge is verified through the implementation of scored tasks in exercises, elaboration of data analysis and implementation of some of the discussed methods in the framework of individual work.

E-learning

Další požadavky na studenta

Additional requirements are not placed on the student.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Exploration data analysis 1. Frequent patterns, Rule based analysis. 2. Representative based clustering, Hierarchical Clustering. 3. Density based clustering, Cluster validation. 4. Self-organizing maps 5. Anomaly detection Data Classification 6. Linear classification (Linear discriminant analysis, Naive Bayes, Logistics regression) 7. Decision Trees, Random Forests. 8. Support Vector Machine, Kernel based methods 9. Neural networks (Perceptron, Feed forward NN+Back propagation) 10. Regression methods 11. Advanced classification methods 12. Classification validation Advanced methods 13. Stream dat analysis 14. Vektor data vizualization

Conditions for subject completion

Full-time form (validity from: 2015/2016 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Graded credit Graded credit 100  51
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2019/2020 (N2647) Information and Communication Technology (1801T064) Information and Communication Security P English Ostrava 2 Optional study plan
2019/2020 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 2 Choice-compulsory study plan
2019/2020 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 2 Choice-compulsory study plan
2019/2020 (N0541A170008) Computational and Applied Mathematics (S01) Applied Mathematics P English Ostrava 2 Compulsory study plan
2019/2020 (N0541A170008) Computational and Applied Mathematics (S02) Computational Methods and HPC P English Ostrava 2 Optional study plan
2019/2020 (N0612A140005) Information and Communication Security P English Ostrava 2 Optional study plan
2018/2019 (N2647) Information and Communication Technology (1801T064) Information and Communication Security P English Ostrava 2 Optional study plan
2018/2019 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 2 Choice-compulsory study plan
2018/2019 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 2 Choice-compulsory study plan
2018/2019 (N2658) Computational Sciences (2612T078) Computational Sciences P English Ostrava 2 Choice-compulsory study plan
2017/2018 (N2647) Information and Communication Technology (1801T064) Information and Communication Security P English Ostrava 2 Optional study plan
2017/2018 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 2 Choice-compulsory study plan
2017/2018 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 2 Choice-compulsory study plan
2017/2018 (N2658) Computational Sciences (2612T078) Computational Sciences P English Ostrava 2 Choice-compulsory study plan
2016/2017 (N2658) Computational Sciences (2612T078) Computational Sciences P English Ostrava 2 Choice-compulsory study plan
2016/2017 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 2 Choice-compulsory study plan
2016/2017 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 2 Choice-compulsory study plan
2016/2017 (N2647) Information and Communication Technology (1801T064) Information and Communication Security P English Ostrava 2 Optional study plan
2015/2016 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 2 Choice-compulsory study plan
2015/2016 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 2 Choice-compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner