In this directory, a notebook is provided to demonstrate how recommendation systems developed in a heterogeneous environment (e.g., Spark, GPU, etc.) can be operationalized.
| Notebook | Description |
|---|---|
| als_movie_o16n | End-to-end examples demonstrate how to build, evaluate, and deploye a Spark ALS based movie recommender with Azure services such as Databricks, Cosmos DB, and Kubernetes Services. |
The diagram below depicts how the best-practice examples help researchers / developers in the recommendation system development workflow.
A few Azure services are recommended for scalable data storage (Azure Cosmos DB), model development (Azure Databricks, Azure Data Science Virtual Machine (DSVM), Azure Machine Learning service), and model operationalization (Azure Kubernetes Services (AKS)).
