IBM today announced a new machine-learning, end-to-end pipeline starter kit for its Cloud Native Toolkit. The big idea here is that wrangling the myriad open-source and enterprise ML and AI platforms and solutions into production can be a challenging prospect. Per IBM‘s developer blog: Moving an application from a Jupyter notebook to a production environment requires numerous components to work together. These components cover a wide range of tasks that developers and administrators have to manage. Developers can spend their time building, training, and deploying models or they can spend all day formatting and wrenching a pipeline together. IBM‘s new…
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