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DataRobot API resources > API user guide > Common use cases > Python v2.x use cases

Python v2.x use cases

Review Jupyter notebooks that outline common use cases and machine learning workflows using DataRobot's Python client.

Topic Describes...
Predict loan defaults A use case that reduces defaults and minimizes risk by predicting the likelihood that a borrower will not repay their loan.
Predict late shipments A use case that determines whether a shipment will be late or if there will be a shortage of parts.
Predict steel plate defects A use case that helps manufacturers significantly improve the efficiency and effectiveness of identifying defects of all kinds, including those for steel sheets.
Reduce 30-Day readmissions rate A use case to reduce the 30-day readmission rate at a hospital.
Measure price elasticity of demand A use case to identify relationships between price and demand, maximize revenue by properly pricing products, and monitor price elasticities for changes in price and demand.
Predict equipment failure A use case that that determines whether or not equipment part failure will occur.
Identify money laundering with anomaly detection How to train anomaly detection models to detect outliers.
Lead scoring A binary classification problem of whether a prospect will become a customer.
Predict fraudulent medical claims The identification of fraudulent medical claims using the DataRobot Python package.
Predict CO₂ levels with out-of-time validation modeling How to use out-of-time validation (OTV) modeling with DataRobot's Python client to predict monthly CO₂ levels for one of Hawaii's active volcanoes, Mauna Loa.
Forecast sales with multiseries modeling How to forecast future sales for multiple stores using multiseries modeling.
Predictions for fantasy baseball An estimate of a baseball player's true talent level and their likely performance for the coming season.
Predict customer churn How to predict customers that are at risk to churn and when to intervene to prevent it.
Configure datetime partitioning How to use datetime partitioning to guard a project against time-based target leakage.
Updated October 11, 2023