The current state of MLOps for machine learning engineers

This article was contributed by Aymane Hachcham, data scientist and contributor to neptune.ai MLOps refers to the operation of machine learning in production. It combines DevOps with lifecycle tracking, reusable infrastructure, and reproducible environments to operationalize machine learning at scale across an entire organization. The term MLOps was first coined by Google in their paper on Machine Learning Operations, although it does have roots in software operations. Google's goal with this paper was to introduce a new approach to developing AI products that is more agile, collaborative, and customer-centric.