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 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.

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 ...

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, ...

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.

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 ...

In this video, Beenish Zia from Intel presents: BigDL Open Source Machine Learning Framework for Apache Spark. "BigDL is a distributed deep learning library for Apache Spark*. Using BigDL, you can ...

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

This report focuses on how to tune a Spark application to run on a cluster of instances. We define the concepts for the cluster/Spark parameters, and explain how to configure them given a specific set ...