sklearn服务器分布式

Sklearn与TensorFlow机器学习实用指南 ——第12章设备和服务器上的分布式TensorFlow...

跨多个参数服务器的分片变量正如我们很快会看到的那样，在分布式设置上训练神经网络时，常见模式是将模型参数存储在一组参数服务器上（即"ps"作业中的任务），而其他任务则集中在计算上（即，"worker"工作中的任务）。对于具有数百万参数...

Sklearn与TensorFlow机器学习实用指南 ——第12章设备和服务器上的分布式TensorFlow...

在第 11 章，我们讨论了几种可以明显加速训练的技术：更好的权重初始化，批量标准化，复杂的优化器等等。但是，即使采用了所有这些技术，在具有单个 CPU 的单台机器上训练大型神经网络可能需要几天甚至几周的时间。在本章中，我们将看到...

Sklearn与TensorFlow机器学习实用指南 ——第12章设备和服务器上的分布式TensorFlow...

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企业级分布式应用服务 EDAS

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