US 11,868,749 B2
Configurable deployment of data science models
Prasad Paravatha, Chicago, IL (US); Vivek Mathew, Schaumburg, IL (US); and Divya Gone, Palatine, IL (US)
Assigned to Discover Financial Services, Riverwoods, IL (US)
Filed by Discover Financial Services, Riverwoods, IL (US)
Filed on Jan. 14, 2022, as Appl. No. 17/576,588.
Prior Publication US 2023/0229412 A1, Jul. 20, 2023
Int. Cl. G06F 8/60 (2018.01); G06F 3/0484 (2022.01); G06F 3/0482 (2013.01)
CPC G06F 8/60 (2013.01) [G06F 3/0482 (2013.01); G06F 3/0484 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A computing platform comprising:
a network interface;
at least one processor;
at least one non-transitory computer-readable medium; and
program instructions stored on the at least one non-transitory computer-readable medium that are executable by the at least one processor such that the computing platform is configured to:
cause a client device associated with a user to display an interface for deploying a new data science model, wherein the interface presents the user with a list of deployment templates, and wherein each of the deployment templates comprises data specifying (i) a respective executable model package and (ii) a respective set of execution instructions for the respective executable model package;
receive, from the client device, data indicating:
a user selection of a given deployment template for use in deploying the new data science model, wherein the given deployment template comprises data specifying:
a given executable model package comprising (i) a trained model object and (ii) a pre-encoded set of pre-processing operations that are available for use with the trained model object; and
a given set of execution instructions for the given executable model package, the given set of execution instructions comprising instructions for (i) which one or more pre-processing operations from the pre-encoded set of pre-processing operations are to be used with the trained model object and (ii) how the one or more pre-processing operations are to be arranged; and
a given set of configuration parameters for use in deploying the new data science model; and
use the given executable model package, the given set of execution instructions for the given executable model package, and the given set of configuration parameters to deploy the new data science model.