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UID:pretalx-cfp-HBJ87V@london2024.pydata.org
DTSTART;TZID=Europe/London:20240615T103000
DTEND;TZID=Europe/London:20240615T111000
DESCRIPTION:Controlled environments such as banks are characterized by stri
 ngent data governance\, model risk policies and operational protocols. The
 se present unique challenges for data science teams to deliver business an
 d customer value. While these constraints manage model and technology risk
 \, they often impede agility and experimentation - key drivers of innovati
 on in data science.\nThis talk discusses how we've managed to scale model 
 training and deployment by 10X with our existing on-prem data science plat
 form.
DTSTAMP:20250709T215830Z
LOCATION:Warwick
SUMMARY:Training and Deployment of ML models at scale in a Risk Controlled 
 Banking Environment - Arun Kundgol\, Aaron Byrne
URL:https://london2024.pydata.org/cfp/talk/HBJ87V/
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