Simple Steps to Distributed Deep Learning: On-Demand Webinar and FAQ Now Available!

Posted Leave a commentPosted in Deep Learning, Horovod, HorovodRunner, Keras, Machine Learning, Platform, Product, PyTorch, TensorFlow

Try this notebook in Databricks On February 12th, we hosted a live webinar—Simple Steps to Distributed Deep Learning on Databricks—with Yifan Cao, Senior Product Manager, Machine Learning and Bago Amirbekian, Machine Learning Software engineer at Databricks. In this webinar, we covered some of the latest innovations brought into the Databricks Unified Analytics Platform for Machine […]

Databricks Runtime 5.2 ML Features Multi-GPU Workflow, Pregel API, and Performant GraphFrames

Posted Leave a commentPosted in Apache Spark, Databricks Runtime 5.2 ML, Deep Learning, Engineering Blog, GraphFrames, HorovodRunner, Machine Learning, Platform, PyTorch, TensorFlow

We are excited to announce the release of Databricks Runtime 5.2 for Machine Learning. This release includes several new features and performance improvements to help developers easily use machine learning on the Databricks Unified Analytics Platform. Continuing our efforts to make developers’ lives easy to build deep learning applications, this release includes the following features […]

Introducing Databricks Runtime 5.1 for Machine Learning

Posted Leave a commentPosted in Announcements, Apache Spark, Company Blog, Databricks Runtime 5.1 ML, Deep Learning, Engineering Blog, Machine Learning, PyTorch, TensorFlow

Last week, we released Databricks Runtime 5.1 Beta for Machine Learning. As part of our commitment to provide developers 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, without […]

A Guide to AI, Machine Learning, and Deep Learning Talks at Spark + AI Summit Europe

Posted Leave a commentPosted in Apache Spark, Company Blog, Deep Learning Pipelines, Events, Keras, PyTorch, Spark + AI Summit, TensorFlow

Within a couple of years of its release as an open-source machine learning and deep learning framework, TensorFlow has seen an amazing rate of adoption. Consider the number of stars on its github page: over 105K; look at the number of contributors: 1500+; and observe its growing penetration and pervasiveness in verticals: from medical imaging […]