BEGIN:VCALENDAR
VERSION:2.0
PRODID:https://github.com/derhansen/sf_event_mgt
METHOD:PUBLISH
BEGIN:VEVENT
UID:115-409@gi.de
CLASS: PUBLIC
SUMMARY:RG Deutsches Eck: Machine Learning and Data Mining for the Credit B
 ureau Industry
DESCRIPTION:\n\nVortragendee: Dr. Thomas Gottron, Dr. Gjergji Kasneci (Schu
 fa Holding AG)\n\nGastgeber: Prof. Dr. Steffen Staab\n\n\n\nTitel: Machine 
 Learning and Data Mining for the Credit Bureau Industry\n\nAbstract: Credit
  bureaus gather, aggregate and analyse information about consumers and busi
 ness entities in order to assess credit related risks. On a methodological 
 and technical level this involves the integration and quality assurance of 
 data from various sources, the analysis of incoming data streams and the ab
 ility to train and apply predictive models. In this talk we will give an ov
 erview of challenging tasks related to use cases in the credit bureau indus
 try and illustrate some modern approaches in the field of machine learning 
 and data mining to address these tasks.\n\n\n\nRaum und Ort: Raum D 239, Ca
 mpus Koblenz, Universität Koblenz-Landau\n\n\n\n
LOCATION:Universität Koblenz-Landau, Campus Koblenz, Raum D 239
DTSTAMP:20180112T132414Z
DTSTART:20180131T150000Z
DTEND:20180131T163000Z
END:VEVENT
END:VCALENDAR