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SUMMARY:Modern CI/CD Machine Learning workflows using Julia - Dhairya Gand
 hi\, Anas Abdelrehim
DTSTART;TZID=Europe/Amsterdam:20240712T120000
DTEND;TZID=Europe/Amsterdam:20240712T123000
DTSTAMP:20260812T150823Z
UID:pretalx-juliacon2024-ZGULY8@pretalx.com
DESCRIPTION:Machine learning model development\, characterized by iterativ
 e experimentation and adjustments\, often leads to complex model iteration
 s\, making tracking and debugging challenging. This talk explores the appl
 ication of CI/CD methodologies to machine learning\, using Julia's Pkg eco
 system\, Buildkite\, GitHub\, and MLflow. We showcase a streamlined proces
 s for efficient model development and tracking that can lead to mass robus
 t experimentation for machine learning workflows
LOCATION:For Loop (3.2)
URL:https://pretalx.com/juliacon2024/talk/ZGULY8/
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