Machine Learning Workbench API

Allows customers to remotely trigger and control the execution of Machine Learning Workbench processes and assets such as data processing, calculations, and schedules.

Use Cases

The Machine Learning Workbench API can be used to:

• Remotely trigger the execution of APIs or machine learning workbench resources via an Action Flow.
• Check the current status of resources for downstream intelligence.

Authentication

This API supports multiple methods of authentication:

• (preferred method) Via OAuth 2.0 token with a scope platform-adoption.tracking-events:read, passed in an HTTP header like this: Authorization: Bearer TOKEN .
• Via Application keys passed in an HTTP header like this: Authorization: AppKey APPLICATION_KEY .
• Via API keys, passed in an HTTP header like this: Authorization: Bearer API_KEY .

See this help page for more information about OAuth 2.0.