Announcing Single-Node Clusters on Databricks
Databricks is used by data teams to solve the world's toughest problems. This can involve running large-scale data processing jobs to extract, transform, and analyze data. However, it often also involves data analysis, data science, and machine learning at the scale of a single machine, for instance using libraries like scikit-learn. To streamline these single...
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...
