Modeling code examples¶
The API user guide includes overviews and workflows for DataRobot's Python client that outline complete examples of common data science and machine learning workflows. Be sure to review the API quickstart guide before using the notebooks below.
| Topic | Describes... |
|---|---|
| Modeling workflow overview | How to use DataRobot's Python client to train and experiment with models. |
| Generate advanced model insights | Model insights available for DataRobot's Python client. |
| Build a model factory | A system or a set of procedures that automatically generate predictive models with little to no human intervention. |
| Configure datetime partitioning | How to use datetime partitioning to guard a project against time-based target leakage. |
| Migrate models | How to transfer models from one DataRobot cluster to another as an .mlpkg file. |
| Feature selection examples | Notebooks that outline Feature Importance Rank Ensembling (FIRE) and advanced feature selection with Python. |