Skip to content

Click in-app to access the full platform documentation for your version of DataRobot.

API user guide

The API user guide includes overviews, Jupyter notebooks, and task-based tutorials that help you find 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... Download link
Modeling workflow overview Learn how to use DataRobot's clients, both Python and R, to train and experiment with models. Python download
R download
Lead scoring Predict whether a prospect will become a customer. You can frame this use case as a binary classification problem. Download
Predict fraudulent medical claims Identify fraudulent medical claims using the DataRobot Python package. Download
Feature Importance Rank Ensembling Learn about 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. Download
Advanced feature selection with R Use R to select features by creating aggregated feature impact. N/A
Build a model factory Create a system or a set of procedures that automatically generate predictive models with little to no human intervention. Download
Prediction Explanation clustering with R Identify and analyze the clusters present in a DataRobot model's Prediction Explanations using the DataRobot R client. N/A
Make Visual AI predictions via the API Configure scripting code for making batch predictions for a Visual AI model via the API. N/A
Get a prediction server ID Learn how to retrieve a prediction server ID using cURL commands from the REST API or by using the DataRobot Python client to make predictions with a deployment. N/A
Using the Batch Prediction API Use DataRobot's batch prediction API to score large datasets with a deployed DataRobot model. Download
Make batch predictions with Azure Blob storage Use the DataRobot Python Client package to set up a batch prediction job that reads an input file for scoring from Azure Blob storage and then writes the results back to Azure. N/A
Make batch predictions with Google Cloud Storage Learn how to read input data from and write predictions back to Google Cloud Storage. N/A

In addition to the examples listed above, DataRobot hosts community-driven notebooks accessible from the following locations:

Resource Description
Examples for data scientists (Github repository) Referential Jupyter notebooks that outline common DataRobot functions.
Tutorials for data scientists (Github repository) Jupyter notebooks that detail applicable use cases for DataRobot.
R vignettes included in the R client Long-form tutorials outlining functions in the DataRobot R package.
Jupyter notebooks included in the Python client Example Jupyter notebooks demonstrating sample use cases and DataRobot functions using the DataRobot Python package.

Updated May 11, 2022
Back to top