Data management for artificial intelligence and machine learning from the perspective of computing environment and user requirements

This course is held in the Czech language.

Annotation

The workshop focuses on the presentation of techniques and procedures necessary for effective work with data in the context of artificial intelligence and machine learning and on the presentation of specific research examples in AI and ML and their requirements or current problems.

During expert-led presentations and discussions, examples of tools and frameworks that facilitate working with datasets and using supercomputing infrastructure to train AI models will be presented. In addition, participants will be able to get insights from researchers from different disciplines on their specific needs and challenges in this area.

Participants from diverse scientific disciplines will have the opportunity to share their experiences and specific requirements related to data management and transfer in the context of their research. The format of the workshop will be highly interactive. Thus, we expect participants to actively participate in discussing and defining the needs of research communities in data management for AI and machine learning.

Level: Advanced

Language: Czech

Tutors:

Jan Martinovič (VŠB-TUO)

Vít Vondrák (VŠB-TUO)

Martin Golasowski (VŠB-TUO) - PDF

Georgy Ponimatkin/ Martin Cífka (ČVUT) - PDF

Rudolf Wittner (MUNI) - PDF

Matej Antol, Teréza Slanináková - PDF, Aleš Křenek (MUNI) - PDF

Vladimír Ulman (VŠB-TUO) - PDF

Michal Kozubek (MUNI) - PDF

Petr Holub (MUNI) - PDF

Mikoláš Jurda (MUNI) - PDF