BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//programme.europython.eu//europython-2023//talk//G9NKUY
BEGIN:VTIMEZONE
TZID:CET
BEGIN:STANDARD
DTSTART:20001029T040000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10
TZNAME:CET
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20000326T030000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3
TZNAME:CEST
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:pretalx-europython-2023-G9NKUY@programme.europython.eu
DTSTART;TZID=CET:20230721T160500
DTEND;TZID=CET:20230721T163500
DESCRIPTION:Music streaming services like Spotify and youtube are famous fo
 r their recommendation systems and each service takes a unique approach to
  recommending and personalize content. While most users are happy with the
  recommendations provided\, there are a section of users who are curious h
 ow and why a certain track is recommended. Complex recommendation systems 
 take various factors like track metadata\, user metadata\, and play counts
  along with the track content itself. \n\nInspired by Andrej Karpathy to b
 uild an own GPT\, we have to use Language Models to build our own music re
 commendation system.
DTSTAMP:20260518T125045Z
LOCATION:Terrace 2A
SUMMARY:Language Models for Music Recommendation - Nischal Harohalli Padman
 abha\, Raghotham Sripadraj
URL:https://programme.europython.eu/europython-2023/talk/G9NKUY/
END:VEVENT
END:VCALENDAR