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Applying Machine Learning (ML) to business applications for automationusually faces difficulties when integrating diverse ML dependencies andservices, mainly because of the lack of a common ML framework. In most cases,the ML models are developed for applications which are targeted for specificbusiness domain use cases, leading to duplicated effort, and making reuseimpossible. This paper presents Acumos, an open platform capable of packagingML models into portable containerized microservices which can be easily sharedvia the platform's catalog, and can be integrated into various businessapplications. We present a case study of packaging sentiment analysis andclassification ML models via the Acumos platform, permitting easy sharing withothers. We demonstrate that the Acumos platform reduces the technical burden onapplication developers when applying machine learning models to their businessapplications. Furthermore, the platform allows the reuse of readily availableML microservices in various business domains.

Packaging and Sharing Machine Learning Models via the Acumos AI Open Platform