Shiny and Environments for R Notebooks
At Databricks, we want the Lakehouse ecosystem widely accessible to all data practitioners, and R is a great interface language for this purpose…
Introducing the Databricks Web Terminal
Introduction We’re excited to introduce the public preview of the Databricks Web Terminal in the 3.25 platform release. Any user with “Can Attach…
%tensorboard – a new way to use TensorBoard on Databricks
Introduction With the Databricks Runtime 7.2 release, we are introducing a new magic command %tensorboard. This brings the interactive TensorBoard experience Jupyter notebook…
Developing Shiny Applications in Databricks
Join our live webinar hosted by Data Science Central on March 12 to learn more We are excited to announce that you can…
Introducing Databricks Runtime 5.4 with Conda (Beta)
We are excited to introduce a new runtime: Databricks Runtime 5.4 with Conda (Beta). This runtime uses Conda to manage Python libraries and…
Accelerating Machine Learning on Databricks: On-Demand Webinar and FAQ Now Available!
On January 15th, we hosted a live webinar—Accelerating Machine Learning on Databricks—with Adam Conway, VP of Product Management, Machine Learning, at Databricks and…
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…
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…
100x Faster Bridge between Apache Spark and R with User-Defined Functions on Databricks
SparkR User-Defined Function (UDF) API opens up opportunities for big data workloads running on Apache Spark to embrace R’s rich package ecosystem. Some…
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…
