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UID:ai1ec-45686@www.spatialsource.com.au
DTSTAMP:20260420T190625Z
CATEGORIES:
CONTACT:https://events.ecmwf.int/event/488/
DESCRIPTION:<div class='ai1ec-event-avatar alignleft timely'><img src='http
 s://www.spatialsource.com.au/wp-content/uploads/2026/03/1759833729532.jpg?
 w=220' width='220' height='215' /></div><p><strong>This ECMWF-ESA Machine 
 Learning Workshop aims to explore the fusion of traditional Earth System O
 bservation and Prediction (ESOP) techniques with machine learning (ML) and
  deep learning (DL) methods.</strong></p>\n<p>It seeks to showcase the imp
 act achieved through this fusion\, while also addressing the remaining cha
 llenges that need further exploration. The presenters will show their cont
 ributions to this field and engage the attendees in discussions to provide
  a comprehensive understanding of the subject. The workshop strongly welco
 mes industry to demonstrate their commercial lenses for ML4ESOP applicatio
 ns.</p>\n<p>This <a href='https://events.ecmwf.int/event/488/' target='_bl
 ank' rel='noopener'>event</a> will delve into the transformative role of M
 L in enhancing data analysis and predictive modelling within atmospheric s
 ciences. Participants will engage with leading experts\, partake in hands-
 on sessions\, and explore cutting-edge innovations that are shaping the fu
 ture of climate research and operational forecasting.</p>\n<p>Tickets: <a 
 class='ai1ec-ticket-url-exported' href='https://events.ecmwf.int/event/488
 /'>https://events.ecmwf.int/event/488/</a>.</p>
DTSTART;TZID=Australia/Sydney:20260413T090000
DTEND;TZID=Australia/Sydney:20260417T170000
LOCATION:Online event
SEQUENCE:0
SUMMARY:Machine Learning for Earth System Observation and Prediction
URL:https://www.spatialsource.com.au/event/machine-learning-for-earth-syste
 m-observation-and-prediction/
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X-TAGS;LANGUAGE=en-US:climate change\,deep learning\,Earth observation\,mac
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X-TICKETS-URL:https://events.ecmwf.int/event/488/
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