Hello,
I am looking to build a multi-tenant machine learning recommender system in Azure Databricks. The idea is to have a single shared model, where each tenant can use the same model to train on their own unique dataset. Essentially, while the model architecture remains the same for all tenants, the data used for training and inference would be specific to each one. Any resources that I can refer or best practices for implementing such a system? Thank you!
