BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//pretalx.com//bbuzz22//speaker//GSE7FN
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-bbuzz22-MGL3ZF@pretalx.com
DTSTART;TZID=CET:20220613T115000
DTEND;TZID=CET:20220613T125000
DESCRIPTION:This case study offers an entertaining way to learn about the p
 ossibilities of stream processing\, which can be applied to projects in fi
 elds that require easy access to current information\, such as finance\, m
 obility and energy. We’ll use the Quix platform to set up a series of op
 en source data sets and code samples that collect\, transform and deliver 
 data under a machine learning model that learns to handle real-time heart 
 rate data. We’ll show how to include complex transformations to the data
 \, such as how to calculate calories burned with Python.
DTSTAMP:20260508T143115Z
LOCATION:Frannz Salon
SUMMARY:Live build: How to harness streaming data in real time to track\, t
 ransform and build on heart rate data - Tomáš Neubauer\, Javier Blanco C
 ordero
URL:https://pretalx.com/bbuzz22/talk/MGL3ZF/
END:VEVENT
END:VCALENDAR