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Lifecycle Models in Machine Learning Development

delete2025-04-01
delete0
PRE
AI
A
A. Crespi
A
Antoni‐Lluís Mesquida *
M
Maria Monserrat
A
Antònia Mas
DOI：10.1111/exsy.70029delete
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Abstract

Abstract

En 中文
Machine Learning (ML) development introduces challenges that traditional software processes often struggle to address. As ML applications grow in complexity and adoption, various lifecycle models have been proposed to address the unique stages of ML development. This study systematically synthesises these models, mapping their stages and activities to provide an understanding of the ML development landscape. The findings highlight research gaps and opportunities, offering insights for advancing academic research and practical implementation.
Keywords:
artificial intelligence
life cycle
lifecycle
machine learning
model

Journal

Expert Systems cover
Expert Systems
IF:
2.3
Papers:
2.5K
Citations:
3.8K

Organization

No organization information available