MLOps – "Why is it required?" and "What it is"? - KDnuggets

Machine Learning (ML) models built by data scientists represent a small fraction of the components that comprise an enterprise production deployment workflow, as illustrated in Fig 1 [1] below. To operationalize ML models, data scientists are required to work closely with multiple other teams such as business, engineering, and operations. This represents organizational challenges in terms of communication, collaboration, and coordination. The goal of MLOps is to streamline such challenges with well-established practices. Additionally, MLOps brings about agility and speed that is a cornerstone in today's digital world.