Calling Azure ML Web Services Using Data Factory

Ginger Grant shows how to call an Azure Machine Learning web service from within Azure Data Factory:

The Linked Service for ML is going to need some information from the Web Service, the URL and the API key. Chances are neither of these have been committed to memory, instead open up Azure ML, go to Web Service and copy them. For the URL, look under the API Help Pagegrid, there are two options, Request/Response and Batch Execution. Clicking on Batch Execution loads a new page Batch Execution API Document. The URL can be found under Request URI. When copying the URL, you do not need to include any text after the word “jobs”. The rest of the URL, “?api-version=2.0”. Copying the entire URL will cause an error. Going back to the web Services page, The API Key appears on the dashboard section of Azure ML and there is a convenient button for copying it. Using these two pieces of information, it is now possible to create the Data Factory Linked Service to make the connection to the web service, which here I called AzureMLLinkedService

Read the whole thing.

Related Posts

Master Data In Azure

Matt How explains why Master Data Services isn’t a great cloud-based master data management solution and offers up an alternative: Excel is easy to use, but not user friendly Excel is on nearly every desktop in any Windows based organisation and with the Master Data Services Add-in, it puts the data well within the reach […]

Read More

Measuring Semantic Relatedness

Sandipan Dey re-works a university assignment on semantic relatedness in Python: Let’s define the semantic relatedness of two WordNet nouns x and y as follows: A = set of synsets in which x appears B = set of synsets in which y appears distance(x, y) = length of shortest ancestral path of subsets A and B sca(x, y) = a shortest common ancestor of subsets A and B This is the notion of […]

Read More

Categories

August 2016
MTWTFSS
« Jul Sep »
1234567
891011121314
15161718192021
22232425262728
293031