Intelligent data analysis
Alapadatok
vimmd294
Course coordinator
associate professor
Szoba: E435
Tel.:
+36 1 463-2677 Email: antal (*) mit * bme * hu |
Lecturers
associate professor
Szoba: E435
Tel.:
+36 1 463-2677 Email: antal (*) mit * bme * hu |
professor emeritus
Szoba: IE437
Tel.:
+36 1 463-2899 Email: tade (*) mit * bme * hu |
![]() professor emeritus
Szoba: IB420
Tel.:
+36 1 463-3595 Email: pataric (*) mit * bme * hu |
Announcements
Introduction
The course provides a systematic overview both about intelligent methods used throughout the data analysis process and about intelligent, complex machine learning schemes used in modern data analysis. Unifying themes of this dual approach, are the Bayesian decision theoretic framework, the network and systems-based approaches, data and knowledge fusion, the use of ontologies and semantic technologies and active, online (reinforcement) learning, which integrate various phases and aspects of data analysis. The course also presents and discusses real-world applications, from the field of biomedicine, pharmaceutical research and system diagnostics.
Submitted by Antal Péter on 2017. September 9. 17:44 | Last updated: 2019. November 7. 13:37