<Session_Outline/>

A tour of the MLOps setup at one of Denmark’s largest pension funds, PensionDenmark. I will go through how we solved a series of challenges concerning versioning, testing, monitoring, and deployment of code and ML models. Our solutions are implemented with Azure DevOps – but the principles apply to other DevOps platforms.

<Key_Takeaways/>

  • How to version code and models.
  • How to automatically train models with the correct code dependencies. 
  • How to score ML models before and during production.
  • How to test deployments before and after deployment.

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<Speaker_Bio/>

Erik Petrovski – Senior Data Scientist | PensionDenmark

I work as a senior data scientist in a small (but growing) team of three data scientists at PensionDenmark, one of Denmark’s largest pension funds. Besides more typical data science model building projects, my responsibilities include many ML engineering tasks with focus on our DevOps/MLOps setup. My educational background is a PhD in quantitative sociology, where I worked on statistical causal effect estimation within nonprofit studies.

May 26 @ 14:45
14:45 — 15:15 (30′)

Day 2 | 19th of May – Engineering

Erik Petrovski – Senior Data Scientist | PensionDenmark