  Applying Machine Learning (ML) to business applications for automation
usually faces difficulties when integrating diverse ML dependencies and
services, mainly because of the lack of a common ML framework. In most cases,
the ML models are developed for applications which are targeted for specific
business domain use cases, leading to duplicated effort, and making reuse
impossible. This paper presents Acumos, an open platform capable of packaging
ML models into portable containerized microservices which can be easily shared
via the platform's catalog, and can be integrated into various business
applications. We present a case study of packaging sentiment analysis and
classification ML models via the Acumos platform, permitting easy sharing with
others. We demonstrate that the Acumos platform reduces the technical burden on
application developers when applying machine learning models to their business
applications. Furthermore, the platform allows the reuse of readily available
ML microservices in various business domains.
