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DTSTAMP:20260808T230116Z
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DESCRIPTION:This course offers basics of analysing datasets with machine le
 arning algorithms and data mining techniques in order to understand founda
 tions of learning from large quantities of data. It starts with general me
 thods for data analysis in order to understand clustering\, classification
 \, and regression. This includes a thorough discussion of test datasets\, 
 training datasets\, and validation datasets required to learn from data wi
 th a high accuracy. Easy application examples will foster the theoretical 
 course elements that also will illustrate problems like overfitting follow
 ed by mechanisms such as validation and regularisation that prevent such p
 roblems.\n The course will start from a very simple application example in
  order to teach foundations like the role of features in data\, linear sep
 arability\, or decision boundaries for machine learning models. In particu
 lar this course will point to key challenges in analysing large quantities
  of data sets (aka ‘big data’) in order to motivate the use of paralle
 l and scalable machine learning algorithms. Hands-on exercises allow the p
 articipants to immediately turn the newly acquired skills into practice. A
 fter this course participants will have a general understanding how to app
 roach data analysis problems in a systematic way including knowledge where
  parallel computing provide benefits.\n About the lecturer: Prof. Dr. – 
 Ing. Morris Riedel received his PhD from the Karlsruhe Institute of Techno
 logy (KIT) and he is the head of the ‘high productivity data processing
 ’ research group of the Juelich Supercomputing Centre (JSC) in Germany. 
 As an adjunct associated professor at the School of Natural Sciences and E
 ngineering of the University of Iceland he teaches ‘High Performance Com
 puting’\, ‘Cloud Computing and Big Data’\, as well as ‘Statistical
  Data Mining’ and all of these courses are on the intersection of parall
 el computing and machine learning. He has given tutorials like the course 
 above at numerous occasions like at the Barcelona Supercomputing Centre\, 
 Smart Data Innovation Conference\, or Prace Spring School in Cyprus. His r
 esearch interests are parallel and scalable machine learning and data scie
 nce. (More info at http://www.morrisriedel.de )\n

LOCATION:Multimediaroom building S9 Campus De Sterre
SUMMARY:Introduction to Machine Learning Algorithms
URL;VALUE=URI:https://www.vscentrum.be/en/education-and-trainings/detail/sp
 ecialist-workshops-in-scientific-computing---swsc-23112017
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