Driverless AI Workflow

A typical Driverless AI workflow is to:

  1. Load data

  2. Visualize data

  3. Run an experiment

  4. Interpret the model

  5. Deploy the scoring pipeline

In addition, you can diagnose a model, transform another dataset, score the model against another dataset, and manage your data in Projects.

Also see the H2O Driverless AI Experiment Setup Wizard, a question and answer workflow that helps automatically set up use case specific experiment settings.

The image below describes a typical workflow.

DAI workflow