Databricks Runtime 5.3 ML Now Generally Available
We are excited to announce the general availability (GA) of Databricks Runtime for Machine Learning, as part of the release of Databricks Runtime 5.3 ML. Built on top of Databricks Runtime, Databricks Runtime ML is the optimized runtime for developing ML/DL applications in Databricks. It offers native integration with popular ML/DL frameworks, such as scikit-learn,...
Introducing Databricks Runtime 5.1 for Machine Learning
Last week, we released Databricks Runtime 5.1 Beta for Machine Learning. As part of our commitment to provide developers with the latest deep learning frameworks, this release includes the best of these libraries. In particular, our PyTorch addition makes it simple for a developer to simply import the appropriate Python torch modules and start coding,...
Introducing Databricks Runtime 5.0 for Machine Learning
Six months ago we introduced the Databricks Runtime for Machine Learning with the goal of making machine learning performant and easy on the Databricks Unified Analytics Platform. The Databricks Runtime for ML comes pre-packaged with many ML frameworks and enables distributed training and inference. Today we are excited to release the second iteration including Conda...
Sharing R Notebooks using RMarkdown
At Databricks, we are thrilled to announce the integration of RStudio with the Databricks Unified Analytics Platform. You can try it out now with this RMarkdown notebook (Rmd | HTML) or visit us at www.databricks.com/rstudio. Introduction Databricks Unified Analytics Platform now supports RStudio Server (press release). Users often ask if they can move notebooks between RStudio and Databricks workspace using...
