DataRobot features an in-depth API that allows data scientists to produce fully automated workflows in their coding environment of choice. Thisaccelerator shows how to enable end-to-end processing of data stored natively in Azure.
About this Accelerator
In this notebook you'll see how data stored in Azure can be used to train a collection of models on DataRobot. You'll then deploy a recommended model and use DataRobot's batch prediction API to produce predictions and write them back to the source Azure container.
What you will learn
Acquiring a training dataset from an Azure storage container
Building a new DataRobot project
Deploying a recommended model
Scoring via batch prediction API
Writing results back to the source Azure container