Configurable deployment of data science models

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.

2. The computing platform of claim 1 , wherein the given set of configuration parameters for deploying the new data science model defines (i) an input dataset for the new data science model and (ii) an output storage location for the new data science model.

3. The computing platform of claim 2 , wherein the given set of configuration parameters for deploying the new data science model further comprises a computing resource allocation to use for deploying the new data science model.

4. The computing platform of claim 1 , wherein the list of deployment templates that is presented to the user is defined based on user permissions assigned to the user.

5. The computing platform of claim 1 , wherein each deployment template in the list of deployment templates is stored within a database.

6. The computing platform of claim 1 , further comprising 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:

after receiving the data indicating the user selection of the given deployment template, cause the interface to present the user with an initial set of configuration parameters corresponding to the given deployment template that is editable by the user, wherein the given set of configuration parameters is defined based at least in part on the initial set of configuration parameters.

7. The computing platform of claim 6 , wherein the initial set of configuration parameters corresponding to the given deployment template is stored within a database.

8. The computing platform of claim 1 , further comprising 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:

track a deployment status of the new data science model; and

while tracking the deployment status of the new data science model, generate an indication of the deployment status that is to be provided to the user.

9. The computing platform of claim 1 , wherein the program instructions that are executable by the at least one processor such that the computing platform is configured to 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 comprise program instructions that are executable by the at least one processor such that the computing platform is configured to:

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 create an executable container comprising the new data science model; and

begin running the executable container.

10. A non-transitory computer-readable medium, wherein the non-transitory computer-readable medium is provisioned with program instructions that, when executed by at least one processor, cause a computing platform 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.

11. The non-transitory computer-readable medium of claim 10 , wherein the given set of configuration parameters for deploying the new data science model defines (i) an input dataset for the new data science model and (ii) an output storage location for the new data science model.

12. The non-transitory computer-readable medium of claim 11 , wherein the given set of configuration parameters for deploying the new data science model further comprises a computing resource allocation to use for deploying the new data science model.

13. The non-transitory computer-readable medium of claim 10 , wherein the list of deployment templates that is presented to the user is defined based on user permissions assigned to the user.

14. The non-transitory computer-readable medium of claim 10 , wherein each deployment template in the list of deployment templates is stored within a database.

15. The non-transitory computer-readable medium of claim 10 , wherein the non-transitory computer-readable medium is also provisioned with program instructions that, when executed by at least one processor, cause the computing platform to:

after receiving the data indicating the user selection of the given deployment template, cause the interface to present the user with an initial set of configuration parameters corresponding to the given deployment template that is editable by the user, wherein the given set of configuration parameters is defined based at least in part on the initial set of configuration parameters.

16. The non-transitory computer-readable medium of claim 15 , wherein the initial set of configuration parameters corresponding to the given deployment template is stored within a database.

17. The non-transitory computer-readable medium of claim 10 , wherein the non-transitory computer-readable medium is also provisioned with program instructions that, when executed by at least one processor, cause the computing platform to:

track a deployment status of the new data science model; and

while tracking the deployment status of the new data science model, generate an indication of the deployment status that is to be provided to the user.

18. A method carried out by a computing platform, the method comprising:

causing 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;

receiving, 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

using 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.