Towards a low-code solution for monitoring machine learning model performance
Panagiotis Kourouklidis, Dimitrios S. Kolovos, Nicholas Matragkas, Joost Noppen · 2020
As the use of machine learning techniques by organisations has become more common, the need for software tools that provide the robustness required in a production environment has become apparent. In this paper, we review relevant literature and outline a research agenda for the development of a low-code solution for monitoring the performance of a deployed machine learning model on a continuous basis.