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SUMMARY:Science and technology seminar: The next 10 years of machine learn
 ing at ECMWF - an introduction to the machine learning roadmap
DTSTART:20210126T100000Z
DTEND:20210126T110000Z
DTSTAMP:20260722T144400Z
UID:indico-event-232@events.ecmwf.int
CONTACT:events@ecmwf.int
DESCRIPTION:\n\nHost\n\n  \n\nFlorence Rabier (ECMWF Director-General)\n
 \nSpeaker\n\n\n\nPeter Dueben (Royal Society University Research Fellow at
  ECMWF)\n\nSeminar overview\n\nMachine learning allows to learn complex\, 
 non-linear behaviour from data which is useful for many application areas 
 across the workflow of numerical weather prediction and climate services. 
 This talk provided an update on the activities at ECMWF to explore the pot
 ential of machine learning\, and in particular deep learning. Peter Dueben
  introduced the machine learning roadmap that identifies challenges\, prov
 ides potential solutions\, and defines steps to channel the many distribut
 ed science and technology projects that study machine learning for weather
  and climate prediction into a coordinated effort. The roadmap will help t
 o make the most of machine learning for weather and climate predictions in
  the years to come.\n\nMachine learning is an important part of ECMWF’s 
 new Strategy 2021–30. The idea is to combine the best of what data-drive
 n approaches can provide with the strengths and physical understanding enc
 apsulated in our existing forecasting systems.\n\nhttps://events.ecmwf.int
 /event/232/
IMAGE;VALUE=URI:https://events.ecmwf.int/event/232/logo-1947851425.png
URL:https://events.ecmwf.int/event/232/
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