Abstract: The described technology is generally directed towards automated development of machine learning pipelines. An automated framework can extract topics from a data science workspace such as a machine learning notebook, transform and annotate cells of the machine learning notebook to various machine learning pipeline stages, and orchestrate the machine learning pipeline stages in a workflow that can be deployed into production data infrastructures.

Abstract: The described technology is generally directed towards automated development of machine learning pipelines. An automated framework can extract topics from a data science workspace such as a machine learning notebook, transform and annotate cells of the machine learning notebook to various machine learning pipeline stages, and orchestrate the machine learning pipeline stages in a workflow that can be deployed into production data infrastructures.

Abstract: The described technology is generally directed towards a machine learning development hub, and corresponding methods and computer readable media. The machine learning development hub can comprise a machine learning development platform complete with various tools for various stages of machine learning development. The machine learning development hub can furthermore comprise translation functions to translate received inputs into inputs to other machine learning development platforms. The machine learning development hub can collect credentials for the other machine learning development platforms and can connect to the other machine learning development platforms via their respective interfaces, in order to supply inputs and instructions thereto. The machine learning development hub can encrypt its communications to other machine learning development platforms to secure its interactions.