<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Distributed on English AI Terms Dictionary</title><link>https://terms-en.ai-term-hub.com/en/tags/distributed/</link><description>Recent content in Distributed on English AI Terms Dictionary</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 18 Jul 2026 11:44:44 +0000</lastBuildDate><atom:link href="https://terms-en.ai-term-hub.com/en/tags/distributed/index.xml" rel="self" type="application/rss+xml"/><item><title>Muse Spark</title><link>https://terms-en.ai-term-hub.com/en/terms/muse_spark/</link><pubDate>Sat, 18 Jul 2026 10:08:54 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/muse_spark/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>Muse Spark is an open-source deep learning framework designed to run efficiently on top of Apache Spark. It allows developers to train complex neural networks across distributed clusters by leveraging Spark&amp;rsquo;s data processing capabilities. This framework simplifies the deployment of machine learning models in big data environments, enabling seamless integration with existing Spark ecosystems for large-scale analytics and inference tasks without requiring separate infrastructure management.&lt;/p>
&lt;h3 id="summary">Summary&lt;/h3>
&lt;p>A distributed deep learning framework built on Apache Spark that enables scalable model training across large clusters.&lt;/p></description></item></channel></rss>