Recommendation engines architecture guidance

Personalized recommendation applications

Generate personalized recommendations for customers in real time, using low-latency and tunable consistency settings for immediate insights.

Build a real-time recommendation API on Azure

This reference architecture shows how to train a recommendation model using Azure Databricks and deploy it as an API by using Azure Cosmos DB and includes a reference implementation on GitHub

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Retail hands-on-lab with recommendation engine

This reference architecture for a retail workload and comes with a complete reference implementation in GitHub.

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