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 […]

How Artificial Intelligence Is Revolutionizing Healthcare Sector in 2019

Posted Leave a commentPosted in AI, AI and machine learning, AI in healthcare, Artificial Intelligence, cognitive computing, Deep Learning, Featured, Machine Learning, Predictive Analytics, SmartData Collective Exclusive

The introduction of so many smart digital technologies like home monitoring devices, wearable sensors, robotic implants, and mobile apps in the healthcare industry have not only improved the effectiveness of care for patients but have also decreased readmission rates and improved the overall quality of life for people all over the world. One of the […]

Accelerating Machine Learning on Databricks: On-Demand Webinar and FAQ Now Available!

Posted Leave a commentPosted in Company Blog, Data Science, Databricks Runtime, Deep Learning, Ecosystem, Engineering Blog, Horovod, HorovodRunner, Keras, Machine Learning, MLflow, Platform, Product, TensorFlow

Try this notebook in Databricks 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 Hossein Falaki, Software Development Engineer and Data Scientist at Databricks. In this webinar, we covered some of the latest innovations brought into the Databricks Unified Analytics Platform […]

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 […]

Can Deep Learning Improve Construction Snag Lists?

Posted Leave a commentPosted in AI, Artificial Intelligence, Big Data, construction, Deep Learning, Machine Learning, SmartData Collective Exclusive, snag list

Big data is changing the future of the construction industry in the United States. Many industry experts and data scientists have talked about some of the ways that big data has changed the industry. Rachel Berger has said that big data has played a role in everything from improving CAD designs to streamlining invoicing. However, […]

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 2019

Posted Leave a commentPosted in AI, Apache Spark, Company Blog, Deep Learning, Events, Machine Learning, Spark + AI Summit

To a good degree, this back-of-the-envelope flowchart, by Karen Hao of MIT Technology Review, charts to elucidate what constitutes the use of AI in the grand scheme of things. source: https://www.technologyreview.com/s/612404/is-this-ai-we-drew-you-a-flowchart-to-work-it-out/ While many conferences may not have a flowchart to select sessions to identify what’s AI, the sessions, though, do speak to technical aspects that […]

Introducing Databricks Runtime 5.0 for Machine Learning

Posted Leave a commentPosted in Announcements, Company Blog, Databricks Runtime 5.0 ML, Deep Learning, Ecosystem, Engineering Blog, Machine Learning, Platform

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 […]

Introducing HorovodRunner for Distributed Deep Learning Training

Posted Leave a commentPosted in Apache Spark, Deep Learning, Distributed Learning, Engineering Blog, Keras, Project Hydrogen, TensorFlow

Today, we are excited to introduce HorovodRunner in our Databricks Runtime 5.0 ML! HorovodRunner provides a simple way to scale up your deep learning training workloads from a single machine to large clusters, reducing overall training time. Motivated by the needs of many of our users who want to train deep learning models on datasets […]

Applying your Convolutional Neural Network: On-Demand Webinar and FAQ Now Available!

Posted Leave a commentPosted in Deep Learning, Ecosystem, Engineering Blog, Keras, Machine Learning, Neural Networks, Platform, TensorFlow

Try this notebook in Databricks On October 25th, we hosted a live webinar—Applying your Convolutional Neural Network—with Denny Lee, Technical Product Marketing Manager at Databricks. This is the third webinar of a free deep learning fundamental series from Databricks. In this webinar, we dived deeper into Convolutional Neural Networks (CNNs), a particular type of neural […]