Organizations can improve performance and reduce costs by replacing the stock Databricks Runtime for Machine Learning libraries with versions optimized by Intel. Here’s how to get started.

With Databricks Machine Learning, new and existing ML capabilities on the Databricks Lakehouse Platform are integrated into a collaborative, purpose-built experience that provides ML engineers ...

Databricks, the Silicon Valley-based startup focused on commercializing Apache Spark, has developed MLflow, an open source toolkit for data scientists to manage the lifecycle of machine learning ...

Amazon, Microsoft, Databricks, Google, HPE, and IBM provide tools for solving a range of machine learning problems, though some toolkits are much more complete than others.

The partnership between Snowflake and Databricks is a welcome sign. It brings best of both the worlds through the combination of an enterprise data warehouse and predictive analytics platforms.

Typical Azure Machine Learning Project Lifecycle (source: Microsoft). At the upcoming Visual Studio Live! @ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will ...

Databricks today unveiled a new cloud-based machine learning offering that’s designed to give engineer everything they need to build, train, deploy, and manage ML models.

Databricks said enterprises have resorted to using a variety of deep learning frameworks, including Tensorflow, Keras and Horovod, to help speed things up, only to find themselves lumbered with ...

Azure SQL Database Machine Learning services preview Support for R models inside SQL Database makes it seamless for data scientists to develop and train models in Azure Machine Learning and deploy ...