Differences Between Shipping Classic Software and Operating ML Models with a Lead MLOps Engineer at TMNL Simon Stiebellehner, and neptune.ai CEO Piotr Niedzwiedz
November 23, 2022
In this episode of MLOps Live, Sabine and Stephen are joined by Simon Stiebellehner, a Lead MLOps Engineer at TMNL (Transaction Monitoring Netherlands). Simon explains how DevOps engineers can transition to MLOps engineers, the approaches MLOps engineers use in creating an ML model, and how a vertical prototype is preferable to a horizontal prototype when test-running a model.
Classical software differs from MLOps due mostly to the model's non-deterministic characteristics. There are significant differences between the design of ML models and that of traditional software; these differences stem mostly from the limits imposed by the time and resources required to test and refine a model prototype before it is put into production. As a result, MLOps engineers will need to put in a lot of effort to overcome these obstacles.
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Previous guests include: Andy McMahon of NatWest Group, Jacopo Tagliabue of Coveo, Adam Sroka of Origami, Amber Roberts of Arize AI, Michal Tadeusiak of deepsense.ai, Danny Leybzon of WhyLabs, Kyle Morris of Banana ML, Federico Bianchi of Università Bocconi, Mateusz Opala of Brainly, Kuba Cieslik of tuul.ai, Adam Becker of Telepath.io and Fernando Rejon & Jakub Zavrel of Zeta Alpha Vector.
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