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# Personalizer simulation in an Azure notebook
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This tutorial simulates a Personalizer loop _system_ which suggests which type of coffee a customer should order. The users and their preferences are stored in a [user dataset](usrs.json). Information about the coffee is also available and stored in a [coffee dataset](coffee.json).
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This tutorial simulates a Personalizer loop _system_ which suggests which type of coffee a customer should order. The users and their preferences are stored in a [user dataset](users.json). Information about the coffee is also available and stored in a [coffee dataset](coffee.json).
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Run the system for 10,000 requests and then create graph showing how fast and accurately the system learned.
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## References
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* [Full sample](https://github.com/Azure-Samples/cognitive-services-personalizer-samples/tree/master/samples/azurenotebook)
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* [Tutorial on docs.microsoft.com](https://docs.microsoft.com/azure/cognitive-services/personalizer/tutorial-use-azure-notebook-generate-loop-data)
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* [Tutorial on docs.microsoft.com](https://docs.microsoft.com/azure/cognitive-services/personalizer/tutorial-use-azure-notebook-generate-loop-data)

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