Examples of using 机器学习系统 in Chinese and their translations into English
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随着机器学习系统在社会的许多领域变得越来越普遍，算法会统治世界，接管我们的思想吗?
As machine learning systems become more common in many areas of society, will algorithms take over the world and our minds?机器学习系统必须要被设计地能够方便地跟踪特性工程和选择的变化。
ML systems must be designed so that feature engineering and selection changes are easily tracked.计算机视觉和其他机器学习系统近期取得的进展是一个原因。
波动的环境：机器学习系统可以适应新数据，并学会在这组新数据中做得很好。
Fluctuating environment: a machine learning system can adapt to new data and 通过让计算机智能地完成特定任务，机器学习系统能通过学习数据执行复杂的流程，而不是提前编程规则。
Through enabling computers to perform specific tasks intelligently, machine learning systems can carry out complex processes by 但是，机器学习系统是被训练来完成特定的任务，因此通常他们的知识不会泛化。
But ML systems are trained to do specific tasks, and typically their knowledge does not generalize.大多数机器学习系统本身并不能解释人类语言，它们不知道为什么人们做出某些决定或是人们接下来打算做什么。
Most machine-learning systems are unable to explain in human terms why they made a decision or what they intend to do next.与任何机器学习系统一样，真正的收益可能出乎我们的预料。
And as with any machine-learning system, the real benefits will likely come from the unexpected.例如第一名的团队，CloudPainter，使用机器学习系统来生成生动艺术作品，有时画出来的是奇异的肖像和风景。
While CloudPainter, the team that stood first, used a machine learning system to generate vivid, sometimes outlandish portraits and landscapes.在下一节中，我将使用三级层次来描述机器学习系统所面临的障碍，这个三级层次管理因果推理中的推理。
In the next section, I will describe the impediments facing machine learning systems using a three-level hierarchy that governs inferences in causal reasoning.大多数机器学习系统通过梳理训练样例并寻找与人类注释器提供的分类相对应的模式来工作。
Most machine-learning systems work by combing through training examples and looking for patterns that correspond to classifications provided by human annotators.但是，机器学习系统是被训练来完成特定的任务，因此通常他们的知识不会泛化。
But ML systems are educated to do specific tasks, and usually their data doesn't generalize.审核发现，该机器学习系统处理的三个文档代码，准确率为98%或99%，远高于人类。
The audit found that the machine learning system was 98 or 99 percent accurate with its three document codes, much better than humans.在亚马逊，我们为支持业务而构建的机器学习系统的公平性，对于建立和维护客户的信任至关重要。
Here at Amazon, the fairness of the machine learning systems we build to support our businesses is critical to establishing and maintaining our customers' trust.个挑战是只是尝试混淆机器学习系统，使其无法正常工作。
One challenge will involve simply trying to confuse a machine-learning system so that it doesn't work properly.机器学习系统将能够检测到由安装在网络摄像头中的恶意软件所引起的Mirai僵尸网络(Miraibotnet)等攻击。
ML systems would have been able to detect attacks such as the Mirai botnet which was caused by malware installed in network cameras.神经网络和其他机器学习系统已经成为21世纪最具颠覆性的技术。
Neural networks and other machine-learning systems have become the most disruptive technology of the 21st century.据他们说，该公司已经开发出一种机器学习系统，可以检测和禁用“不当行为”账户。
According to them, the company has developed a machine learning system that detects and disables'inappropriate behavior' accounts.机器学习系统无法解释它们的想法，这意味着你的算法可能因错误的原因而表现良好。
Machine learning systems can't explain their thinking, and that means your algorithm could be performing well for the wrong reasons.该机器学习系统，它横空出世，是正确的-至少，当它来到靶心和岛形图案，他们之后。
The machine-learning system, it turned out, was correct--at least when it came to the bull's-eye and island patterns they were after.
