Skip to content

On-premise users: click in-app to access the full platform documentation for your version of DataRobot.

NextGen UI documentation > AI experimentation

AI experimentation

The following sections provide details for creating Workbench machine learning and time series experiments:

Topic Description
Create and evaluate predictive experiments Create non-time series (predictive) experiments, both supervised or unsupervised. Fine-tune experiment setup, making row-by-row predictions based on your data.
Create and evaluate time-aware experiments Create supervised or unsupervised experiments and fine-tune experiment setup, using time-relevant data to make row-by-row predictions, time series forecasts, or current value predictions "nowcasts".
Manage experiments Access the data insights and the model Leaderboard to evaluate and compare models and experiments.
Evaluate with model insights View model insights to interpret, explain, and validate what drives a model predictions.
Make predictions After you create an experiment and train models, you can upload scoring data, make predictions, and download the results.
Experiment reference Provide reference content that supports working with predictive and time-aware experiments.
Updated March 26, 2025