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TRAINING A MACHINE LEARNING ALGORITHM TO PREDICT WHEN COMPUTING DEVICES MAY HAVE ISSUES

机译:培训机器学习算法以预测计算设备可能存在问题

摘要

In some examples, a server may use machine learning to determine, based on service requests associated with multiple computing devices, that a component included in the multiple computing devices is predicted to fail at a particular date. The server may use the machine learning to determine, based on the particular date and an expiration date of a warranty associated with the computing devices, that a customer may initiate a service request on a predicted service date. The machine learning may determine recommended solutions including purchasing an extended warranty, purchasing extended services (e.g., on-site service), purchasing a depot clinic service, or trading in the multiple computing devices for newer computing devices. In response to receiving a purchase order to purchase at least one of the recommended solutions, the server may initiate at least one of the recommended solutions.
机译:在一些示例中,服务器可以使用机器学习基于与多个计算设备相关联的服务请求来确定包括在多个计算设备中的组件被预测在特定日期失败。 服务器可以使用机器学习基于与计算设备相关联的保修的特定日期和到期日期确定,客户可以在预测服务日期发起服务请求。 机器学习可以确定推荐的解决方案,包括购买扩展保修,购买扩展服务(例如,现场服务),购买Depot Clinic Service,或在多个计算设备中进行交易,用于较新的计算设备。 响应于接收到购买至少一个推荐解决方案的采购订单,服务器可以启动至少一个推荐的解决方案。

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