5 Reasons to Become an Apache Spark Expert
Apache Spark ™ has fast become the most popular unified analytics engine for big data and machine learning. It was originally developed at...
Apparate: Managing Libraries in Databricks with CI/CD
This is a guest blog from Hanna Torrence, Data Scientist at ShopRunner. Introduction As leveraging data becomes a more vital component of organizations'...
Kicking Off 2019 with an MLflow User Survey
It’s been six months since we launched MLflow , an open source platform to manage the machine learning lifecycle, and the project has...
Introducing Databricks Library Utilities for Notebooks
Databricks has introduced a new feature, Library Utilities for Notebooks, as part of Databricks Runtime version 5.1. It allows you to install 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 Built-in Image Data Source in Apache Spark 2.4
Introduction With recent advances in deep learning frameworks for image classification and object detection, the demand for standard image processing in Apache Spark...
Apache Avro as a Built-in Data Source in Apache Spark 2.4
Try this notebook in Databricks Apache Avro is a popular data serialization format. It is widely used in the Apache Spark and Apache...
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...
MLflow v0.8.0 Features Improved Experiment UI and Deployment Tools
Last week we released MLflow v0.8.0 with multiple new features, including improved UI experience and support for deploying models directly via Docker containers...
Introducing HorovodRunner for Distributed Deep Learning Training
Today, we are excited to introduce HorovodRunner in our Databricks Runtime 5.0 ML ! HorovodRunner provides a simple way to scale up your...