Announcing General Availability of Databricks Model Serving
ML Virtual Event Enabling Production ML at Scale With Lakehouse March 14, 9 AM PDT / 4 PM GMT Register Now We are...
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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...
MLflow v0.8.0 Features Improved Experiment UI and Deployment Tools
Last week we released MLflow v0.8.0 with multiple new features, including improved UI experience and support for deploying models directly via Docker containers...
MLflow v0.7.0 Features New R API by RStudio
Today, we’re excited to announce MLflow v0.7.0 , released with new features, including a new MLflow R client API contributed by RStudio...
New Features in MLflow v0.6.0
Today, we’re excited to announce MLflow v0.6.0 , released early in the week with new features. Now available on PyPI and Maven...
New Features in MLflow v0.5.2 Release
Today, we’re excited to announce MLflow v0.5.0, MLflow v0.5.1, and MLflow v0.5.2, which were released last week with some new features. MLflow 0.5.2...
MLflow 0.4.2 Released
Today, we’re excited to announce MLflow v0.4.0, MLflow v0.4.1, and v0.4.2 which we released within the last week with some of the recently...
MLflow v0.3.0 Released
Today, we’re excited to announce MLflow v0.3.0, which we released last week with some of the requested features from internal clients and open...
Cloud-based Relational Database Management Systems at Databricks
Databricks and Microsoft have jointly developed a new cloud service called Microsoft Azure Databricks , which makes Apache Spark analytics fast, easy, and...
Declarative Infrastructure with the Jsonnet Templating Language
This blog post is part of our series of internal engineering blogs on Databricks platform, infrastructure management, integration, tooling, monitoring, and provisioning. At...
Next Generation Physical Planning in Apache Spark
Never underestimate the bandwidth of a station wagon full of tapes hurtling down the highway. — Andrew Tanenbaum, 1981 magine a cold, windy...