Building and deploying a machine learning model with automated ML on Azure. - WebSystemer.no

We click on our newly deployed model and will find see a list of attributes, of which the relevant one is the "Scoring URI". Remember talking about API endpoints? This Scoring URI is our endpoint for the model we have created, meaning we can send ("do a request") something to this endpoint (input) and will receive a response (output). And if we format the request correctly, we will get back what we want: a price per night estimate given our input columns. This part might get a bit confusing for those who have no experience working with HTTP requests, but just keep following the steps and you'll get it to work!