Machine learning is about making data-driven decisions or predictions based on existing data. Apache Spark and its machine learning library MLlib offer several algorithms useful for developing ...

To help solve this problem, Spark provides a general machine learning library — MLlib — that is designed for simplicity, scalability, and easy integration with other tools.

While last week's Spark Summit was relatively short on news, just wait for the next wave as developers get their hands dirtier with machine learning.

Spark ML brings efficient machine learning to large compute clusters and combines with TensorFlow for deep learning ...

In this fourth installment of Apache Spark article series, author Srini Penchikala discusses machine learning concepts and Spark MLlib library for running predictive analytics using a sample ...

Spark can coordinate multiple computers to work in tandem. IBM already offers a number of platform services based on machine learning algorithms, such as language translation and data visualization.

The AMPLab this week announced the release of KeystoneML, a framework for building and deploying large-scale machine-learning pipelines within Apache Spark. While the software is still in alpha stage, ...

Apache Spark creators set out to standardize distributed machine learning training, execution, and deployment ...

Databricks, the primary commercial steward behind the popular open source Apache Spark project, published a new report indicating the technology is still red-hot, driven by more use of SQL, streaming ...

LinkedIn continues its strategy of developing hot technology and open-sourcing it, this time a machine learning library for Spark called Photon ML.