
ML platform teams, features stores, versioning in data pipelines, and where MLOps extends DevOps with Aurimas Griciūnas and Piotr Niedźwiedź
ML Platform Podcast
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DevOps and Machine Learning
Every DevOps practice can be applied to MLOps when it comes to deployment. Machine learning applications, however, are a little bit harder to monitor in production because they're not deterministic. So you need to attach additional things like training pipelines which well naturally they are not part of DevOps as software engineers don't do that.
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