# Predictive experiments
URL: https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/index.html

> Create machine learning and time series experiments and iterate quickly to evaluate and select the best predictive and forecasting models.

# Predictive experiments

The following sections provide details for creating non-time, time-aware, and time series experiments:

| Topic | Description |
| --- | --- |
| Create and evaluate non-time-aware 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 using time-relevant data, and fine-tune experiment setup, make 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. |
| No-code applications | Create and configure AI-powered applications using a no-code interface to enable core DataRobot services. |
| 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. |

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