Reputation: 429
I wanted to know how exactly the following works in backend
Scenario :
-> We get data from Edgex foundry in UTC format and we it store it in Azure Document DB in (CST/CDT timezone) format
-> We trained ML model on data(with Date in CST/CDT timezone) and Deploy web service.
So I have few basic doubts below
When web job hits our predictive webservice , will the trained ML model be run again?
Do we need to convert the UTC timezone for new incoming test data( which we want to predict) into CST/CDT timezone, as TimeStamp does matter for our prediction?
What happens in backend when predictive webservice API is called?
Upvotes: 0
Views: 114
Reputation: 2784
This is only based on my experience with Azure ML, but I think I can help with your questions.
When web job hits our predictive webservice, will the trained ML model be run again?
Yes, in the sense that it will call the predict
(or similar) method on the model on the new data. For instance, in scikit-learn
you would train your model using the fit
method. Once the model is in production, only the predict
method would be called.
It will also run the whole workflow you have set up to be deployed as the web service. As an example below is a workflow I've played around with before. Each time the web service is run with new data, this whole thing will be run. This is like creating a Pipeline in scikit-learn
.
Do we need to convert the UTC timezone for new incoming test data( which we want to predict) into CST/CDT timezone, as TimeStamp does matter for our prediction?
I would say yes, you would need to convert to the timezone that was used when training in the model. This can be done by adding a step in your workflow then when you call the web service it will do the necessary converting for you before making a prediction.
What happens in backend when predictive webservice API is called?
I'm not sure if anyone knows for sure other than the folks at Microsoft, but for sure it will run the workflow you have set up.
I know it's not much, but I hope this helps or at least gets you on the right track for what you need.
Upvotes: 1