Development_and_Deployment_of_ML_based_systems-10.pdf (139.67 kB)
Download file

Practices and Infrastructures for ML Systems – An Interview Study

Download (139.67 kB)
posted on 10.11.2021, 04:36 by Dennis MuiruriDennis Muiruri, Lucy Ellen Lwakatare, Jukka K. Nurminen, Tommi Mikkonen

The best practices and infrastructures for developing and maintaining machine learning (ML) enabled software systems are often reported by large and experienced data-driven organizations. However, little is known about the state of practice across other organizations. Using interviews, we investigated practices and tool-chains for ML-enabled systems from 16 organizations in various domains. Our study makes three broad observations related to data management practices, monitoring practices and automation practices in ML model training, and serving workflows. These have limited number of generic practices and tools applicable across organizations in different domains.


Email Address of Submitting Author

ORCID of Submitting Author


Submitting Author's Institution

University of Helsinki

Submitting Author's Country


Usage metrics