JFrog announces partnership with AWS to streamline secure ML model deployment. January 17, 2024. ... With MLflow, Databricks says organizations will be able to package code for reproducible runs, ...

Databricks, the Silicon Valley-based startup focused on commercializing Apache Spark, has developed MLflow, an open source toolkit for data scientists to manage the lifecycle of machine learning ...

MLflow, the open source framework for managing machine learning (ML) experiments and model deployments, has stabilized its API, and reached a version 1.0 milestone, now generally available.

And today, to build on that, Databricks is announcing the addition of the MLflow Model Registry and a private preview release of it integrated into the UDAP. Also read: AI gets rigorous ...

Databricks’ MLflow offering already has the ability to log metrics, parameters, and artifacts as part of experiments, package models and reproducible ML projects, and provide flexible deployment ...

Databricks has added new features to MLflow to make it easy to integrate with mainstream CI/CD (continuous integration, continuous deployment) tools such as Jenkins and GitLab.

The service integrates with other lakehouse services, including Databricks Feature Store for automated online lookups, MLflow Model Registry for model deployment, Unity Catalog for unified ...

MLflow, With More Than 140 contributors And 800K Monthly Downloads, Now Offers Users A Central Model Repository To Accelerate Machine Learning Deployments AMSTERDAM & SAN FRANCISCO–(BUSINESS ...