Chapter 8: Model Scoring and Deployment
In the previous chapter, we learned how to use outputs generated by DataRobot to understand models and why a model provides a particular prediction. We will now learn how to use models to score input datasets and create predictions to be used in the intended applications. DataRobot automates many tasks that are required for scoring and generating row-level explanations.
Creating predictions, however, is not where these tasks end. In most cases, these predictions need to be transformed into actions for consumption by people or applications. This mapping of predictions to actions requires an understanding of business and therefore needs a person to interpret the results (in most use cases). In this chapter, we will discuss how this is done. We're going to cover the following main topics:
- Scoring and prediction methods
- Generating prediction explanations
- Analyzing predictions and postprocessing
- Deploying DataRobot models...
