Machine Learning Operations (MLOps): Overview, Definition, and Architecture. (arXiv:2205.02302v1 [cs.LG])

Web: http://arxiv.org/abs/2205.02302

The final goal of all industrial machine learning (ML) projects is to develop
ML products and rapidly bring them into production. However, it is highly
challenging to automate and operationalize ML products and thus many ML
endeavors fail to deliver on their expectations. The paradigm of Machine
Learning Operations (MLOps) addresses this issue. MLOps includes several
aspects, such as best practices, sets of concepts, and development culture.
However, MLOps is still a vague term and its consequences for researchers and …

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