Reflecting on Initiating an Azure Machine Learning Pipeline with HTTP Request
What objects are required to initiate an Azure Machine Learning pipeline using an HTTP request?
a. An authorization header that includes the subscription ID for the Azure Machine Learning workspace
b. An authorization header with a token for a service principal that has permission to run the pipeline
c. A JSON payload that specifies the experiment name
d. A JSON payload that specifies the compute target for the pipeline
Answer:
In order to initiate an Azure Machine Learning pipeline using an HTTP request, you need to provide: an authorization header with a token for a service principal permitted to run the pipeline, and a JSON payload specifying the experiment name.
When initiating an Azure Machine Learning pipeline through an HTTP request, certain objects need to be provided to ensure a successful execution. These objects include:
Authorization Header:
An important object required is an authorization header containing a token for a service principal authorized to run the pipeline. This ensures that the request is valid and authenticated.
JSON Payload:
Additionally, a JSON payload indicating the experiment name must be included. This specifies the specific experiment under which the pipeline will be executed.
It's crucial to have the correct authorization credentials and payload information in place to effectively trigger the Azure Machine Learning pipeline via an HTTP request. By providing these essential objects, you can seamlessly initiate the desired pipeline for your machine learning projects.