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 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.

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

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 ...

MLflow, Databricks' Open Source MLOps framework, is leaving the nest. Meanwhile, Delta Engine puts some new spring into Spark SQL's step.

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.

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.

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