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An Empirical Evaluation of Flow Based Programming in the Machine Learning Deployment Context. (arXiv:2204.12781v1 [cs.SE])
cs.LG updates on arXiv.org arxiv.org
As use of data driven technologies spreads, software engineers are more often
faced with the task of solving a business problem using data-driven methods
such as machine learning (ML) algorithms. Deployment of ML within large
software systems brings new challenges that are not addressed by standard
engineering practices and as a result businesses observe high rate of ML
deployment project failures. Data Oriented Architecture (DOA) is an emerging
approach that can support data scientists and software developers when
addressing such …
arxiv context deployment evaluation flow learning machine machine learning programming