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Authors: Cristiana Moroz-Dubenco ; Bogdan-Eduard-Mădălin Mursa and Mátyás Kuti-Kreszács

Affiliation: Faculty of Mathematics and Computer Science, Babeş-Bolyai University, Cluj Napoca, Romania

Keyword(s): Collaborative Development, Machine Learning Systems, Automatization.

Abstract: The field of Artificial Intelligence (AI) has rapidly transformed from a buzzword technology to a fundamental aspect of numerous industrial software applications. However, this quick transition has not allowed for the development of robust best practices for designing and implementing processes related to data engineering, machine learning (ML)-based model training, deployment, monitoring, and maintenance. Additionally, the shift from academic experiments to industrial applications has resulted in collaborative development between AI engineers and software engineers who have reduced expertise in established practices for creating highly scalable and easily maintainable processes related to ML models. In this paper, we propose a series of good practices that have been developed as the result of the collaboration between our team of academic researchers in AI and a company specializing in industrial software engineering. We outline the challenges faced and describe the solutions we des igned and implemented by surveying the literature and deriving new practices based on our experience. (More)

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Paper citation in several formats:
Moroz-Dubenco, C. ; Mursa, B. and Kuti-Kreszács, M. (2023). Towards Good Practices for Collaborative Development of ML-Based Systems. In Proceedings of the 18th International Conference on Software Technologies - ICSOFT; ISBN 978-989-758-665-1; ISSN 2184-2833, SciTePress, pages 604-611. DOI: 10.5220/0012130500003538

@conference{icsoft23,
author={Cristiana Moroz{-}Dubenco and Bogdan{-}Eduard{-}Mădălin Mursa and Mátyás Kuti{-}Kreszács},
title={Towards Good Practices for Collaborative Development of ML-Based Systems},
booktitle={Proceedings of the 18th International Conference on Software Technologies - ICSOFT},
year={2023},
pages={604-611},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012130500003538},
isbn={978-989-758-665-1},
issn={2184-2833},
}

TY - CONF

JO - Proceedings of the 18th International Conference on Software Technologies - ICSOFT
TI - Towards Good Practices for Collaborative Development of ML-Based Systems
SN - 978-989-758-665-1
IS - 2184-2833
AU - Moroz-Dubenco, C.
AU - Mursa, B.
AU - Kuti-Kreszács, M.
PY - 2023
SP - 604
EP - 611
DO - 10.5220/0012130500003538
PB - SciTePress

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