Tensor Input Now Supported in MLflow
Traditionally, generic MLflow Python models only supported DataFrame input and output. While DataFrames are a convenient interface when dealing with classical models built...
Page 1
Quickly Deploy, Test, and Manage ML Models as REST Endpoints with MLflow Model Serving on Databricks
MLflow Model Registry now provides turnkey model serving for dashboarding and real-time inference, including code snippets for tests, controls, and automation. MLflow Model...
Announcing MLflow Model Serving on Databricks
Databricks MLflow Model Serving provides a turnkey solution to host machine learning (ML) models as REST endpoints that are updated automatically, enabling data...
Introducing Built-in Image Data Source in Apache Spark 2.4
Introduction With recent advances in deep learning frameworks for image classification and object detection, the demand for standard image processing in Apache Spark...