Machine Learning Lifecycle Management

A system for managing a lifecycle of a machine learning (ML) application from a provider point of view, the system comprising:

• one or more data processors;
• and
• memory storing instructions stored on at least one of the one or more data processors, which when executed, results in operations comprising:
• generating, within a data intelligence platform, a package comprising ML scenarios and a training pipeline, wherein the training pipeline comprises training logic associated with a defined workflow for training the ML application;
• synchronizing, via an application programming interface, the data intelligence platform with a first database;
• generating, by the first database, a transport request comprising the package, the transport request facilitating publication of content from the ML application;
• assembling the ML application from the transport request within a second database;
• and
• displaying ML content on a graphical user interface associated with the second database.

A non-transitory computer program product storing instructions which, when executed by at least one data processor forming part of at least one computing device, implement operations comprising:

• generating, within a data intelligence platform, a package comprising ML scenarios and a training pipeline, wherein the training pipeline comprises training logic associated with a defined workflow for training the ML application;
• synchronizing, via an application programming interface, the data intelligence platform with a first database;
• generating, by the first database, a transport request comprising the package, the transport request facilitating publication of content from the ML application;
• assembling the ML application from the transport request within a second database;
• and
• displaying ML content on a graphical user interface associated with the second database.