The managed MLflow integration with Databricks on Google Cloud requires Databricks Runtime for Machine Learning 8.1 or above.
Databricks provides a rich collection of tools to help you develop machine learning applications. However, finding these tools and understanding how best to apply them to your machine learning problems can be difficult. The reference solutions provided on this page show detailed examples of how you can use Databricks for some common machine learning applications.
This article contains a reference solution for distributed image model inference based on a common setup shared by many real-world image applications.
This article contains a reference solution for how to build a wide-and-deep model for a recommender system, and how to serve it on Databricks.