SAP SE
Machine Learning Lifecycle Management

Abstract:

Systems, methods, and computer program products for managing a lifecycle of a machine learning (ML) application from a consumer point of view are described herein. Execution of an intelligent scenario for training of the ML application is initiated. An integrator component generates a training pipeline. The training pipeline includes training logic associated with a defined workflow for the training. An application having an input dataset trains the ML application using the training pipeline. The integrator component determines training metrics associated with the trained ML application. The training metrics are indicators of a level of accuracy of the trained ML application. A centralized component provides the training metrics for characterization of the trained model.