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Smart Manufacturing: Seagate's Global Deployment of Defect Detection System with MLOps Automation
技术
- 分析与建模 - 机器学习
- 基础设施即服务 (IaaS) - 混合云
适用行业
- 水泥
- 教育
适用功能
- 设施管理
- 产品研发
用例
- 施工管理
- 基础设施检查
服务
- 云规划/设计/实施服务
- 培训
挑战
希捷面临着效率低下、孤立的手动工作流程以及混合云资源利用不足的挑战。他们有很长的 Python 脚本,必须手动执行,导致开发延迟。他们的工作流程中断,并且混合云基础设施的服务器利用率较低。他们需要一个基础设施来自动化管道组件并提高效率。
关于客户
希捷科技是数据存储和管理解决方案的全球领导者。他们拥有一支由数据科学专业人员和机器学习工程师组成的团队,他们构建先进的深度学习脚本来解决业务问题。 Seagate 的高级分析小组负责在全球范围内的制造工厂部署缺陷检测系统。
解决方案
Seagate 实施 cnvrg.io 作为应对挑战的解决方案。 cnvrg.io 提供了一个端到端流程,可以自动化 MLOps 管道,连接其混合云基础设施并允许他们同时运行多个云。它简化并加速了 ML 管道,提高了资源利用率,并实现了 ML 管道组件的自动化。希捷还受益于云爆发、混合云支持、模型训练和评估、模型管理、大规模协作、模型监控、模型再训练和数据管理等功能。
运营影响
数量效益
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