Databricks is excited to announce that Managed MLflow is generally available on Azure Databricks and it will use Azure Machine Learning to track the full ML lifecycle.

Microsoft is joining the Databricks-backed MLflow project for machine learning experiment management. Already present in Azure Databricks, a fully managed version of MLflow will be added to Azure ...

Databricks says MLflow now has over 100 contributors, and has been deployed at thousands of organizations. Add to that participation from Microsoft and support for MLflow in its Azure Machine ...

Databricks Runtime for ML is meant to eliminate the complexities of distributed computing needed for deep learning. The company also introduced GPU support for AWS and Microsoft Azure to make it ...

With MLflow project becoming a part of the Linux Foundation, it will witness increased adoption from ML platform providers, framework and tool developers and enterprises.

MLflow also gains integrations with popular machine learning libraries and frameworks such as SciKit-Learn, TensorFlow, Keras, PyTorch, H2O and Apache Spark Mllib, Databricks said.

Locking down AI pipelines in Azure? A zero-trust, metadata-driven setup makes it secure, scalable and actually team-friendly.

Microsoft and Databricks have actually worked on this integration since 2016, and this is making Databricks a first-party service on Azure.

Databricks Inc. opens its Data + AI Summit today with the announcement that it will release the entirety of its Delta Lake storage framework to open-source under the oversight of the Linux ...