Demystifying MLOps
Abstract
Data scientists have an intuition of what goes into training a machine learning model, but building an MLOps strategy to deploy that model can sound daunting for data science teams. Model services are not one-size-fits-all, so it is imperative to know a range of tools available. One option, Vetiver, is a framework for R and Python created to make model deployment feel like a natural extension of a data scientist’s skill set.
This talk offers a high-level overview of what MLOps options are available for model operationalization, but also shows a practical example of an end-to-end MLOps deployment of a model-aware REST API using Vetiver.
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This was SUCH a fun conference to go to! The warmth and sense of community in the R world is so apparent; they were pretty accepting of me, a Pythonista 😉. This talk brings the ways you can deploy models into the mechanics of baking cookies.
P.S. Here is the shirt I wear in this talk, which reads, “Rage against the Machine Learning”. This is not an affiliate link (but it probably should be after this shirt got so much love at the conference).