Neptune.ai > 实例探究 > 使用 Neptune 改善体育数据分析的管道管理和性能

使用 Neptune 改善体育数据分析的管道管理和性能

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技术
  • 分析与建模 - 机器学习
  • 应用基础设施与中间件 - 中间件、SDK 和库
适用行业
  • 设备与机械
  • 石油和天然气
适用功能
  • 质量保证
用例
  • 计算机视觉
  • 视觉质量检测
服务
  • 测试与认证
  • 培训
关于客户
ReSpo.Vision 是一家在体育数据分析中使用计算机视觉和机器学习的公司。他们向足球行业的球员、球探、经理、俱乐部和联合会提供从单视图摄像机体育广播视频中提取的 3D 数据。
挑战
ReSpo.Vision 在大规模管理和调试大量管道方面面临挑战。他们努力解决调试问题、跟踪管道结果以及重现成功的实验。
解决方案
该团队实施了 Neptune,这是一个与现有框架 Kedro 集成的工具。 Neptune 提供了一个集中平台,用于管理管道运行、调试错误和比较结果。它还提供直观的 UI,用于向非技术利益相关者报告管道质量并监控计算使用情况。
运营影响
  • The integration of Neptune into ReSpo.Vision’s workflow resulted in significant operational benefits. The team gained control over their process, with all the information needed to debug any experiment in one place. They could easily compare pipelines, assess the outputs’ performance and quality, and confidently decide which models were the best. They also leveraged the summary statistics provided by Neptune to know what pipelines they should run based on the output of previous runs and if there were issues with the last run. Additionally, they used Neptune’s intuitive UI to communicate pipeline results to clients and other stakeholders who are not technical. They also used Neptune’s compute monitoring capability to make the most of the compute used by their pipelines. This resulted in optimized processes, minimized costs, and improved customer satisfaction due to higher quality data.

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