Subject description - XP36VPD

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XP36VPD Selected Parts of Data Mining
Roles:S Extent of teaching:2P+2S
Department:13136 Language of teaching:
Guarantors:Kléma J. Completion:ZK
Lecturers:Kléma J. Credits:4
Tutors:Kléma J. Semester:

Anotation:

Data mining aims at revealing non-trivial, hidden and ultimately applicable knowledge in large data. This course focuses on two key data mining issues: data size and their heterogeneity. When dealing with large data, it is important to resolve both the technical issues such as distributed computing or hashing and general algorithmic complexity. In this part, the course will be motivated mainly by case studies on web and social network mining. The second part will discuss approaches that merge heterogeneous prior knowledge with measured data. Bioinformatics will make the main application field here. It is assumed that students have completed the master course on Machine Learning and Data Analysis (A4M33SAD).

Content:

Data mining aims at revealing non-trivial, hidden and ultimately applicable knowledge in large data. This course focuses on two key data mining issues: data size and their heterogeneity. When dealing with large data, it is important to resolve both the technical issues such as distributed computing or hashing and general algorithmic complexity. In this part, the course will be motivated mainly by case studies on web and social network mining. The second part will discuss approaches that merge heterogeneous prior knowledge with measured data. Bioinformatics will make the main application field here. It is assumed that students have completed the master course on Machine Learning and Data Analysis (A4M33SAD).

Course outlines:

Exercises outline:

Literature:

Anand Rajaraman, Jure Leskovec, Jeffrey D. Ullman: Mining of Massive Datasets, Cambridge University Press, 2011.

Requirements:

Webpage:

https://cw.fel.cvut.cz/wiki/courses/xp36vpd/start

Subject is included into these academic programs:

Program Branch Role Recommended semester
DOKP Common courses S
DOKK Common courses S


Page updated 27.10.2020 17:52:06, semester: Z,L/2020-1, L/2019-20, Z/2021-2, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)