Executing modeling experiments with DataRobot
DataRobot currently provides two ways to execute modeling experiments: DataRobot Classic and Workbench. Workbench is where an experiment will be managed under a use case, focusing on extracting value from a use case more seamlessly, and DataRobot Classic is the original AutoML experience where a modeling experiment is called a project. A project, or a modeling experiment here, encompasses the same components, which include modeling machine learning, gathering model insights and prediction insights, and making one-off batch predictions. We will dive deeper into these three components.
Deep learning modeling
DataRobot provides modeling configurations and tasks in the form of directed acyclic graphs (DAG) called blueprints. The individual nodes in the graph are grouped up into the following:
- Input data: The input nodes can be any of the supported input data types.
- Data preprocessing tasks: They consist of data regularization...
