Deploying a deep learning blueprint
DataRobot allows the deployment of a model directly through a trained blueprint in an experiment or a project, which we will explore in the next practical section. However, for more advanced users, the platform also allows the deployment of custom models through the Custom Model Workshop feature. Custom inference models are user-created, pre-trained models that can be uploaded to DataRobot as a collection of files coupled with either a drop-in environment or by a requirements.txt file. Once uploaded, users can create, test, and deploy custom inference models to DataRobot’s centralized deployment hub. These custom models support different model types, which include regression, classification, and unstructured types where the input and output can be of various types.
To ensure the reliability and compatibility of your custom models, DataRobot provides a comprehensive testing suite in the Custom Model Workshop. The custom model testing suite...
