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SUMMARY:#Hack4BestCX: Predictive Maintenance with Machine Learning
DTSTART;TZID=Europe/Berlin:20240301T090000
DTEND;TZID=Europe/Berlin:20240301T210000
DTSTAMP:20260413T142631Z
UID:9984d1b877b54a4bb516cdf758f2108f@www.medfak.uni-bonn.de
CREATED:20240125T085305Z
DESCRIPTION:How can you and ML help to further enhance prediction models a
 t Telekom?\nDeutsche Telekom\, the Transfer Center enaCom at the Universit
 y of Bonn and the Lamarr Institute for Machine Learning and Artificial Int
 elligence are looking for innovative and unconventional solutions to this 
 question at the #Hack4BestCX hackathon to improve Customer Experience (CX)
 . Thanks to predictive maintenance\, we can easily check the status of div
 erse net components and detect disruptions at an early stage. At #Hack4Bes
 tCX your team will work on a specific challenge within one day being suppo
 rted by Deutsche Telekom data scientists and based on Telekom's operating-
  and performance data. The aim is to develop prediction models which recog
 nize failures or deviations in the net performance as precisely as possibl
 e. The winners will receive vouchers worth up to 250 EUR and all participa
 nts will receive exclusive goodies!
LAST-MODIFIED:20240125T092650Z
URL:https://www.medfak.uni-bonn.de/de/fakultaet/veranstaltungen/transfer/h
 ack4bestcx-predictive-maintenance-with-machine-learning
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