Quality Assurance in MLOps Setting: An Industrial Perspective. (arXiv:2211.12706v1 [cs.SE])

Today, machine learning (ML) is widely used in industry to provide the core
functionality of production systems. However, it is practically always used in
production systems as part of a larger end-to-end software system that is made
up of several other components in addition to the ML model. Due to production
demand and time constraints, automated software engineering practices are
highly applicable. The increased use of automated ML software engineering
practices in industries such as manufacturing and utilities requires an …

arxiv industrial mlops perspective quality quality assurance