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VERSION:2.0
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BEGIN:VEVENT
SUMMARY:Forecasting Renewable Energy Production Using Machine Learning
DTSTART;VALUE=DATE-TIME:20260710T094000Z
DTEND;VALUE=DATE-TIME:20260710T101000Z
DTSTAMP;VALUE=DATE-TIME:20260702T234216Z
UID:indico-contribution-215-1160@events.grnet.gr
DESCRIPTION:Speakers: Anestis  Ampatzidis (EY & AUTH)\nThis presentation f
 ocuses on Day-Ahead forecasting of solar energy production\, showcasing a 
 practical application of Machine Learning in renewable energy. The discuss
 ion covers the complete data pipeline\, detailing how meteorological and h
 istorical records are processed to train predictive ML models\, particular
 ly Neural Networks. Additionally\, the role of Aggregators (FOSE) in the m
 odern energy market is examined to emphasize the real-world value of accur
 ate forecasting. Finally\, the design of an intuitive User Interface (UI) 
 tailored for visualizing these predictions is presented\, offering a compl
 ete perspective from raw data to the final end-user experience.\n\nhttps:/
 /events.grnet.gr/event/215/contributions/1160/
LOCATION:
URL:https://events.grnet.gr/event/215/contributions/1160/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Concepts of Machine Learning & Deep Learning
DTSTART;VALUE=DATE-TIME:20260710T091000Z
DTEND;VALUE=DATE-TIME:20260710T094000Z
DTSTAMP;VALUE=DATE-TIME:20260702T234216Z
UID:indico-contribution-215-1159@events.grnet.gr
DESCRIPTION:Speakers: Vasileios  Kochliaridis (AUTH)\nThis topic introduce
 s concepts of Machine Learning and Deep Learning\, with a focus on time-se
 ries forecasting. The talk explains how systems can learn patterns from da
 ta and make predictions without relying on explicit programming. It then f
 ocuses on Deep Learning\, which can model complex relationships in large d
 atasets\, with a special emphasis on forecasting models for time-series da
 ta. The webinar covers modern deep learning methods\, including LSTMs\, GR
 Us\, Temporal Convolutional Networks and Transformers. Participants will g
 ain a clear overview of how these models are used in real-world applicatio
 ns such as finance and energy.\n\nhttps://events.grnet.gr/event/215/contri
 butions/1159/
LOCATION:
URL:https://events.grnet.gr/event/215/contributions/1159/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Introduction & Objectives
DTSTART;VALUE=DATE-TIME:20260710T090000Z
DTEND;VALUE=DATE-TIME:20260710T091000Z
DTSTAMP;VALUE=DATE-TIME:20260702T234216Z
UID:indico-contribution-215-1158@events.grnet.gr
DESCRIPTION:Speakers: Ioannis  Vlahavas (AUTH)\nhttps://events.grnet.gr/ev
 ent/215/contributions/1158/
LOCATION:
URL:https://events.grnet.gr/event/215/contributions/1158/
END:VEVENT
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