Skip to content

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

DataRobot API resources > AI accelerators > Use cases and horizontal approaches > Build a recommendation engine

Build a recommendation engine

Access this AI accelerator on GitHub

The accelerator provided in this notebook trains a model on historical customer purchases in order to make recommendations for future visits. The DataRobot features that will be utilized in this notebook are multi-Label modeling and feature discovery. Together the resulting model can provide rank ordered suggestions of content, product, or services that a specific customer might like.

In the notebook, you will:

  • Analyze the datasets required
  • Create a multilabel dataset for training
  • Connect to DataRobot
  • Configure a feature discovery project
  • Generate features and models
  • Generate recommendations for new visits
Updated September 28, 2023