"MLOps or ML Ops is a set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently."
MLOps 는 프로덕션 환경에서 머신러닝 학습 모델을 안정적이고 효율적으로 배포하고,
유지관리 하는 것을 목표로 하는 것
ref: Breuel, Cristiano. "ML Ops: Machine Learning as an Engineering Discipline". Towards Data Science. Retrieved 6 July 2021.
ref: google, Hidden Technical Debt in Machine Learning Systems. NIPS.
Sculley, D & Holt, Gary & Golovin, Daniel & Davydov, Eugene & Phillips, Todd & Ebner, Dietmar & Chaudhary, Vinay & Young, Michael & Dennison, Dan. (2015). Hidden Technical Debt in Machine Learning Systems. NIPS. 2494-2502.
ref: Walsh, Nick. "The Rise of Quant-Oriented Devs & The Need for Standardized MLOps". Slides. Nick Walsh. Retrieved 1 January 2018.