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Recommendation Engine with DataRobot's MultiLabel

Recommendation Engine with DataRobot's MultiLabel

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 modelling 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:

  1. Analyze the datasets required
  2. Create a multi-label dataset for training
  3. Connect to DataRobot
  4. Configure a feature discovery project
  5. Generate features and models
  6. Generate recommendations for new visits
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