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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2023/2024

Selected Parts of Data Mining

The course is not on the list Without time-table
Code Completion Credits Range
XP36VPD ZK 4 2P+2S
Garant předmětu:
Lecturer:
Tutor:
Supervisor:
Department of Computer Science
Synopsis:

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).

Requirements:
Syllabus of lectures:
Syllabus of tutorials:
Study Objective:
Study materials:

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

Note:
Further information:
https://cw.fel.cvut.cz/wiki/courses/XP36VPD
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2024-07-25
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