The two companies’ data science platforms have become core components for many CIOs who are focused on leveraging ...

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’ cloud-based platform is powered by Apache Spark, the most popular open source technology for big data processing and machine learning workloads, and is an invention of the co ...

Databricks Runtime for Machine Learning includes the stock versions of scikit-learn and TensorFlow. To boost performance, however, Intel engineers replaced these versions with Intel-optimized ...

Moreover, Databricks' recent fundraising round and financial revelations may also indicate both its value as a start-up and ...

Unified Data Governance: Manage and govern all data and ML assets with Unity Catalog, including those consumed and produced by model serving. Databricks is committed to driving innovation with its ...

Data analytics developer Databricks Inc. today announced the general availability of Databricks Model Serving, a serverless real-time inferencing service that deploys real-time machine learning ...

To fix this, Databricks is introducing a new machine learning toolkit called “MLflow,” which is designed to help companies better package machine learning code, execute it and test it, and ...

The end-to-end machine learning workflow was first introduced to the industry this year at Spark + AI Summit in San Francisco. MLflow is an open source, cross-cloud framework that can dramatically ...

Databricks Machine Learning provides each member of the data team with the right tools in one collaborative environment. Users can switch between Data Science / Engineering, SQL Analytics, and the new ...