BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:Africa/Algiers
BEGIN:STANDARD
DTSTART:19810501T010000
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:CET
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BEGIN:VEVENT
DTSTAMP:20261027T161139Z
UID:2B7C7C5D-0F32-4B3D-927A-BAC65E8FD92D
DTSTART;TZID=Africa/Algiers:20261028T140000
DTEND;TZID=Africa/Algiers:20261028T160000
DESCRIPTION:This hands-on workshop explores how to process noisy sensor dat
 a\, recognize unusual patterns\, and identify previously unseen anomalies 
 using modern machine learning approaches. Through interactive experiments 
 with real-world data\, participants will discover how to build more adapti
 ve and reliable IoT systems.\n\nSpeaker(s): Farah Hammami\n\nFaculty of Sc
 iences of Bizerte\, Zarzouna\, Bizerte\, Tunisia
LOCATION:Faculty of Sciences of Bizerte\, Zarzouna\, Bizerte\, Tunisia
ORGANIZER:ras-fsb@ieee.tn
SEQUENCE:12
SUMMARY: Modern Techniques for Anomaly Detection in IoT
URL;VALUE=URI:https://events.vtools.ieee.org/m/589325
X-ALT-DESC:Description: <br /><p>This hands-on workshop explores how to pro
 cess noisy sensor data\, recognize unusual patterns\, and identify previou
 sly unseen anomalies using modern machine learning approaches. Through int
 eractive experiments with real-world data\, participants will discover how
  to build more adaptive and reliable IoT systems.</p>
END:VEVENT
END:VCALENDAR