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Machine Learning mit Scikit-Learn
--client
pyconde
--show
pyconde2012
--room saal2 1429 --force
Next: 11 EnArgus - ein ontologiebasiertes Forschungsinformationssystem
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Marks
Author(s):
Andreas Müller
Location
Saal 2
Date
oct Tue 30
Days Raw Files
Start
13:30
First Raw Start
13:28
Duration
00:30.0:00
Offset
0:01:33
End
14:00
Last Raw End
14:01
Chapters
00:00
0:21:27
Total cuts_time
27 min.
https://2012.de.pycon.org/programm/schedule/sessions/26/
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Machine Learning und Data Mining beschaeftigen sich mit dem Lernen aus beobachteten Daten, dem erstellen von Vorhersagen und dem finden von interessanten Mustern in Daten. Diese Gebiete sind zwei schnell wachsende Forschungsbereiche mit einer staendig steigenden Anzahl an kommerziellen Anwendungen wie Produkt-Empfehlungen, Bildersuche und Spam-Filtering. Scikit-learn ist eine Python Library fuer Machine Learning die besonderen Wert auf einfache Benutzung, Skalierbarkeit und hohe Code-Qualitaet legt. Ziel ist es eine leicht anzuwendende, flexible Bibliothek fuer Forschung wie auch kommerzielle Anwendungen zu schaffen. Der Vortrag bietet eine kurze Einleitung in Grundlagen des maschinellen Lernens und die Anwendung von Scikit-Learn.
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