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
Read more and deploy solution
To learn more about building personaled recommendation applications in Azure Cosmos DB, check out these resources.
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