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UID:pretalx-pyconde-pydata-berlin-2023-CTKC7B@pretalx.com
DTSTART;TZID=CET:20230419T122500
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DESCRIPTION:This talk presents a novel approach to MLOps that combines the 
 benefits of open-source technologies with the power and cost-effectiveness
  of cloud computing platforms. By using tools such as Terraform\, MLflow\,
  and Feast\, we demonstrate how to build a scalable and maintainable ML sy
 stem on the cloud that is accessible to ML Engineers and Data Scientists. 
 Our approach leverages cloud managed services for the entire ML lifecycle\
 , reducing the complexity and overhead of maintenance and eliminating the 
 vendor lock-in and additional costs associated with managed MLOps SaaS ser
 vices. This innovative approach to MLOps allows organizations to take full
  advantage of the potential of machine learning while minimizing cost and 
 complexity.
DTSTAMP:20260309T204950Z
LOCATION:A1
SUMMARY:Maximizing Efficiency and Scalability in Open-Source MLOps: A Step-
 by-Step Approach - Paul Elvers
URL:https://pretalx.com/pyconde-pydata-berlin-2023/talk/CTKC7B/
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