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• X Session 0 :: Warm-up is_parent of Order of the day (ID: 7693 :: weight 100) :: TEXTREC ::
  
  
  • 10:00 - 10:15 :: Digitales Ankommen
  
  
  • Introduction
  
  
  • Course overview
  
  
  • Machine-learning intro
  
  
  • Jupyter intro
  
  
  • Warm-up exercise (in break-out rooms ??)
  
  
  • Discussion
  
  
  • Warm-up exercise (in break-out rooms ??)
  
  
  • Discussion
  
  
• X Session 0 :: Warm-up is_parent of Who am I ? (Daniel) (ID: 5669 :: weight 90) :: TEXTREC ::
  • founder of oldest Slovak digital community kyberia.sk
  • Bc. in humanities (Charles University in Prague) and Bc. in linguistics (Universite de Nice Sophia-Antipolis)
  • MSc. in cognitive sciences (Ecole Pratique des Hautes Etudes, Paris)
  • PhDs. in psychology (Universite Paris 8) and cybernetics (Slovak University of Technology)
  • ex IT-Admin of UdK's Medienhaus
  • Digital Education juniorprofessor (Einstein Center Digital Future / UdK)
• X Session 0 :: Warm-up is_parent of Who am I ? (Paul) (ID: 7694 :: weight 89) :: TEXTREC ::
  • Artist and Programmer
  • Wissenschaftlicher Mitarbeiter von Daniel
  • BA in Visuelle Kommunikation
  • plsdlr.net
• X Session 0 :: Warm-up is_parent of Who am I ? (Nik) (ID: 7695 :: weight 89) :: TEXTREC ::
  • Artist and Electrical Engineer
  • Studentische Hilfskraft von Daniel
  • BA in Electrical Engineering / KuM Absolvent(Almost)
• X Session 0 :: Warm-up is_parent of M.O.D.E.A #4 : (Machine) learning and data (science) (ID: 7633 :: weight 80) :: TEXTREC ::
  In this course, we are going to follow some nice O'Reilly data science manual and, line by line, learn about meaning of terms like "feature", "multi-class classification", "training" and "cross validation" and, while doing so, acquire all necessary prerequisities of "the most sexy job of 22nd century".
  
  We start this Friday (24th April) at 10:00 am
• X Session 0 :: Warm-up is_parent of What is this course NOT about ? (ID: 7703 :: weight 77) :: TEXTREC ::

  it is not about neural networks *

  
  

  it is not about "regression"

  
  

   

  
  

  * well, it will be also about neural networks, but just a little bit ;)

• X Session 0 :: Warm-up is_parent of What is this course about ? (ID: 7702 :: weight 75) :: TEXTREC ::

  about learning

  
  

  about classification

  
  

  about main machine learning concepts: true positive / true negative / false positive / false negative / feature, feature extraction, classifier, accuracy etc.

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