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Amazon Personalize Data Science

Diagnostics

Open the diagnose/ folder to find an example on how to approach visualization of the key properties of your input datasets.

The key components we look out for include:

  • Missing data, duplicated events, and repeated item consumptions
  • Power-law distribution of categorical fields
  • Temporal drift analysis for cold-start applicability
  • Analysis on user-session distribution

Offline Performance Evaluation

Open the offline_performance_evaluation/ folder to find an example on how to approach the offline evaluation of your Amazon Personalize Campaign recommendations.

License Summary

This sample code is made available under a modified MIT license. See the LICENSE file.