Introducing the Next-Generation Data Science Workspace
At today’s Spark + AI Summit 2020, we unveiled the next generation of the Databricks Data Science Workspace: An open and unified experience for modern data teams. Existing solutions make data teams choose from three bad options. Giving data scientists the freedom to use any open-source tools on their laptops doesn’t provide a clear path...
MLflow Joins the Linux Foundation to Become the Open Standard for Machine Learning Platforms
Watch Spark + AI Summit Keynotes here At today's Spark + AI Summit 2020, we announced that MLflow is becoming a Linux Foundation project. Two years ago, we launched MLflow, an open source machine learning platform to let teams reliably build and productionize ML applications. Since then, we have been humbled and excited by the...
A Guide to the MLflow Talk at Spark + AI Summit 2020
It's been 2 years since we originally launched MLflow, an open source platform for the full machine learning lifecycle, and we are thrilled and humbled by the adoption and impact it has gained in the data science and data engineering community. With now over 2M+ monthly downloads, 200 code contributors and over a 100 contributing...
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 now develop and test Shiny applications in Databricks! Inside the RStudio Server hosted on Databricks clusters, you can now import the Shiny package and interactively develop Shiny applications. Once completed, you can...
Databricks Named A Leader in Gartner Magic Quadrant for Data Science and Machine Learning Platforms
Gartner has released its 2020 Data Science and Machine Learning Platforms Magic Quadrant, and we are excited to announce that Databricks has been recognized as a Leader. Gartner evaluated 17 vendors for their completeness of vision and ability to execute. We are confident the following attributes contributed to the company's success: Our unique ability to...
Deep Learning Tutorial Demonstrates How to Simplify Distributed Deep Learning Model Inference Using Delta Lake and Apache Spark™
On October 10th, our team hosted a live webinar—Simple Distributed Deep Learning Model Inference—with Xiangrui Meng, Software Engineer at Databricks. Model inference, unlike model training, is usually embarrassingly parallel and hence simple to distribute. However, in practice, complex data scenarios and compute infrastructure often make this "simple" task hard to do from data source to...
A Day at the 2019 Women in Product Conference
From left to right: Shveta, Julia, Yardley Pohl (a WIP board member and co-founder), Anna, Allie, Cyrielle, and Rani at the Databricks booth Databricks was a proud sponsor of the 2019 Women In Product conference which focuses on empowering women in product management and advocating for equal representation. We had a booth and happy hour...
Introducing the MLflow Model Registry
Watch the announcement and demo At today’s Spark + AI Summit in Amsterdam, we announced the availability of the MLflow Model Registry, a new component in the MLflow open source ML platform. Since we introduced MLflow at Spark+AI Summit 2018, the project has gained more than 140 contributors and 800,000 monthly downloads on PyPI, making...
A Guide to Women In Unified Analytics Events at Spark+AI Summit Europe
Spark + AI Summit is Europe’s largest data and machine learning conference, and the big news in 2019 is how many women are driving some of the greatest advances in big data, machine learning, and data science. This 15-17 October in Amsterdam, more than 1700 data scientists, engineers, and developers will gather to share best...
A Guide to MLflow Talks at Spark + AI Summit 2019 Europe
We are thrilled to see how well MLflow has been welcomed by the community since we launched it last summer. With now over 800K monthly downloads, 130 code contributors and dozens of contributing organizations including RStudio and Microsoft, it is one of the fastest growing open source projects in the field of Machine Learning, confirming...
