Automatic Suggestion of Variation Parameters & Pre-Packaged Synthetic Datasets

One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations comprising:

• pre-packaging a synthetic dataset tailored for training a first machine learning scenario;
• receiving, from a distributed Synthetic Data as a Service (SDaaS) interface, a selection of the first machine learning scenario from a plurality of machine learning scenarios;
• causing presentation, on the SDaaS interface, of an indication of the availability of the pre-packaged synthetic dataset for the selected machine learning scenario;
• receiving, via the SDaaS interface, a selection to download the pre-packaged synthetic dataset;
• and
• providing access to the pre-packaged synthetic dataset.

A method for suggesting variation parameters for machine learning, the method comprising:

• receiving, from a distributed Synthetic Data as a Service (SDaaS) interface, a selection of a machine learning scenario from a plurality of machine learning scenarios;
• retrieving, from a seeding taxonomy that associates the plurality of machine learning scenarios with corresponding subsets of a plurality of variation parameters, a subset of variation parameters associated with the selected machine learning scenario by the seeding taxonomy;
• causing presentation of the subset of variation parameters, on the SDaaS interface, as suggested variation parameters for the selected machine learning scenario;
• receiving, from the SDaaS interface, a selection of variation parameters from the plurality of variation parameters and an associated frameset generation request;
• and
• generating a corresponding frameset package with frames that vary the selected variation parameters.