MACHINE LEARNING APPLICATIONS - 翻译成中文

• 机器学习应用
• 的机器学习应用程序

在 英语 中使用 Machine learning applications 的示例及其翻译为 中文

Today, the majority of networking design activity is in the cloud, much of which is is being driven by artificial intelligence and machine learning applications.
今天，大多数网络设计活动都在云端，其中大部分都是由AI和机器学习应用驱动的。

Our platform is uniquely designed to enable the rapidly growing data science community and machine learning applications.
我们平台的独特设计旨在赋能快速增长的数据科学社区和机器学习应用。

It offers an excellent collection of well-tested libraries and techniques for developing machine learning applications.
它提供了用于开发机器学习应用程序的出色库和技术的绝佳集合。

Building well performing machine learning applications requires highly specialized data scientists and domain experts.
通常，构建表现优良的机器学习应用，需要非常专业的数据科学家和领域专家。

There are many machine learning applications for which a domain specific language(DSL) is the perfect solution.
在许多机器学习应用程序中，领域特定语言(DSL)是完美的解决方案。

They suffer from major weaknesses in areas like advanced semiconductors to support machine learning applications.
它们在用以支持机器学习应用的先进半导体等领域存在重大弱点。

In addition, machine learning applications in such settings need to be designed to run“continuously” for months on end(e.g., without memory leaks).
另外，这类环境中的机器学习应用程序必须能够数月“连续”运行（不会发生内存泄漏等故障）。

So the question is: what performance hit will we see in machine learning applications?
所以问题是:我们在机器学习应用程序中会看到什么样的性能影响?

Machine learning applications try to find hidden patterns and correlations in the chaos of large data sets to develop models that can predict behaviour.
机器学习应用程序试图在大数据集的混乱中找出隐藏的模式和相关性，从而开发能够预测行为的模型。

Thanks to machine learning applications, more and more devices now feature object recognition capabilities.
由于机器学习的应用，越来越多的物联网设备现在具有了物体识别功能。

Machine learning applications can help medical organizations improve customer service, extract value from large data amounts, efficiently analyze medical records, and enhance patient treatment.
机器学习应用程序可以帮助医疗机构改善客户服务、从大量数据中提取有价值信息、高效分析医疗记录并改善患者治疗。

Increasing deployment of artificial intelligence and machine learning applications that utilize massive amounts of data and compute resources and often require generating real-time results.
增加使用大量数据和计算资源的人造智能和机器学习应用程序的部署，并且通常需要生成实时结果。

Once again, software-based machine learning applications are adding the intelligence aspect to the cars.
又一次，基于软件的机器学习应用为汽车带来了智能功能。

In many real-world machine learning applications, AutoML is strongly needed due to the limited machine learning expertise of developers.
赛事概述：在许多真实世界的机器学习应用中，由于开发人员的机器学习专业知识有限，所以这时候AutoML非常重要。

The development of data science and machine learning applications, for example, requires the use of large volumes of training data.
例如，数据科学和机器学习应用程序的发展需要使用大量的训练数据。

Now go forth and wield your understanding of algorithms to create machine learning applications that make better experiences for people everywhere.
现在，您将了解算法，以创建机器学习应用程序，为各地的人们提供更好的体验。

However, developing successful machine learning applications requires a substantial amount of“black art” that is hard to find in textbooks.
然而，如果想开发成功的机器学习应用，你需要使用大量难以在教科书中找到的「魔法」。

As with most machine learning applications, progress in emotion detection depends on accessing more high-quality data.
与大多数机器学习应用程序一样，情绪检测的进展取决于访问更高质量的数据。

Machine learning applications find hidden patterns and correlations in the chaos of large data sets to develop models that can predict behavior.
机器学习应用程序试图在大数据集的混乱中找出隐藏的模式和相关性，从而开发能够预测行为的模型。

Though, developing effective machine learning applications need a considerable amount of“black art” that is not that easy to find in manuals.
尽管如此，开发有效的机器学习应用需要大量的“黑魔法”，这在手册中很难找到。