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Python 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...
Feature Importance Rank Ensembling The benefits of Feature Importance Rank Ensembling (FIRE)—a method of advanced feature selection that uses a median rank aggregation of feature impacts across several models created during a run of Autopilot.
Advanced feature selection with Python How to select features by creating aggregated feature impact.
Build a model factory A system or a set of procedures that automatically generate predictive models with little to no human intervention.
Make Visual AI predictions via the API Scripting code for making batch predictions for a Visual AI model via the API.
Configure datetime partitioning How to use datetime partitioning to guard a project against time-based target leakage.
Using the Batch Prediction API DataRobot's batch prediction API to score large datasets with a deployed DataRobot model.
Make batch predictions with Azure Blob storage How to generate SHAP-based Prediction Explanations with a use case that determines what drives home value in Iowa.
Make batch predictions with Google Cloud Storage How to read input data from and write predictions back to Google Cloud Storage.
Python client troubleshooting Cases that can cause issues with using the Python client and known fixes.

Updated October 11, 2022
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