In DataRobot, the way you deploy a model to production depends on the type of model you start with and the prediction environment where the model will be used. The following sections describe how to add deployments for different types of artifacts, including models built in DataRobot, custom inference models, and remote models.
|Deploy a DataRobot model||Deploying a DataRobot model from the Leaderboard or the Model Registry.|
|Deploy a custom inference model||Deploying a custom inference model from the Custom Model Workshop.|
|Deploy an external model||Deploying an external (remote) model from the Model Registry or by uploading training data and deploying from the deployment inventory.|
|Add deployment information||How to complete a deployment by configuring inference options.|
|Add prediction data post-deployment||Adding historical prediction data to an existing deployment.|