...
首页> 外文期刊>JMLR: Workshop and Conference Proceedings >Flexible and Scalable Deep Learning with MMLSpark
【24h】

Flexible and Scalable Deep Learning with MMLSpark

机译:使用MMLSpark灵活和可扩展的深度学习

获取原文
           

摘要

In this work we detail a novel open source library, called MMLSpark, that combines the flexible deep learning library Cognitive Toolkit, with the distributed computing framework Apache Spark. To achieve this, we have contributed Java Language bindings to the Cognitive Toolkit, and added several new components to the Spark ecosystem. In addition, we also integrate the popular image processing library OpenCV with Spark, and present a tool for the automated generation of PySpark wrappers from any SparkML estimator and use this tool to expose all work to the PySpark ecosystem. Finally, we provide a large library of tools for working and developing within the Spark ecosystem. We apply this work to the automated classification of Snow Leopards from camera trap images, and provide an end to end solution for the non-profit conservation organization, the Snow Leopard Trust.
机译:在这项工作中,我们详细介绍了一个名为MMLSpark的新颖开源库,它将灵活的深度学习库认知工具包组合在一起,分布式计算框架Apache Spark。为实现这一目标,我们为认知工具包贡献了Java语言绑定,并将多个新组件添加到火花生态系统中。此外,我们还将流行的图像处理库OpenCV与Spark集成,并为任何SparkML估算器提供了自动生成Pyspark包装器的工具,并使用此工具将所有工作揭露给Pyspark生态系统。最后,我们提供了一个大型工具库,用于在火花生态系统内工作和发展。我们将这项工作应用于来自相机陷阱图像的雪豹的自动分类,并为非利润节约组织提供结束解决方案,雪豹信任。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号