Examples of using 学习应用程序 in Chinese and their translations into English
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这有助于理解GPU的价值，因为GPU加速了深度学习应用程序所需的张量（tensor）处理。
It helps to understand that the GPU is valuable because it accelerates the tensor(math) processing necessary for deep learning applications.深度学习应用程序的训练数据通常决定其功能的范围和限度。
The training data of a deep learning application often determines the scope and limit of its functionality.NVIDIA深度学习SDK提供了强大的工具和资料库，专门服务于设计及部署GPU加速深度学习应用程序，其中包括逻辑回归。
The NVIDIA Deep 但是，您不能仅仅将数据转储到机器学习应用程序中，然后就期望得到高质量的结果--甚至是有用的结果。
But you cannot just dump your data into a machine learning application and expect high-quality results- or even useful ones.据官方网站声称，Mahout项目的目的是“为迅速构建可扩展、高性能的机器学习应用程序打造一个环境。
According to its website, the Mahout project's goal is"to build an environment for quickly creating scalable performant machine learning applications.".例如，使用这种灵活的计算解决方案的深入学习应用程序可以减少15%的能耗，根据我们的初步实验。
For example, a deep learning application using this flexible computing solution could reduce energy consumption by 15%, according to our preliminary experiment.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。
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.这就是为什么NASA和亚马逊合作使用新的机器学习应用程序，以更好地预测太阳“超级风暴”的到来的原因。
That's why NASA and Amazon are teaming up with a new machine learning application to better predict the coming of a solar“superstorm.”.例如，她说智能扬声器，如Alexa或GoogleHome，可以直接在设备上运行语音识别和一些机器学习应用程序。
For instance, she says smart speakers, such as Alexa or Google Home, could run speech recognition and some machine learning applications directly on the device.领先的探路者：荷兰皇家航空公司(KLM)已成为首个部署采用人工智能的深度学习应用程序的主要消费者品牌。
A leading indicator: KLM Royal Dutch Airlines has become the first major consumer brand to deploy an AI-infused deep learning application.通过利用分布式网络，在云中进行深度学习让您可以更快地设计、开发和培训深度学习应用程序。
By leveraging distributed networks, deep 我假设您或您的团队正在开发一个机器学习应用程序，并且您希望快速取得进展。
I assume that you or your team is working on a machine learning application, and that you want to make rapid progress.构建AI数据存储可能很困难，因为必须考虑存储网络和调优存储以与机器学习应用程序协同工作的其他因素。
Building AI data storage can be hard, as additional factors must be considered for storage networking and tuning storage to work with machine learning applications.去年，美国食品和药物管理局（FDA）批准了第一个医疗机器学习应用程序ArterysCardioDL。
Last year, the U.S. Food and Drug Administration(FDA) approved the first machine learning application for healthcare: The Arterys Cardio DL.Mahout是一个开源框架，设计用于构建可拓展的机器学习应用程序，它有以下三个显著的特点：.
Mahout is an open-source framework designed for building scalable machine learning applications, it has three prominent features listed below.例如，AndreyBulezyuk使用Python编程语言创建了一个很牛逼的机器学习应用程序。
(For example, Andrey Bulezyuk used the Python programming language to create an amazing machine learning application.).它是一个可用于图像分类的工具包，不擅长其他的深度学习应用程序，如文字或语音。
It can be used like a toolkit for image classification, while not for other deep learning application such as text or speech.步骤2:学习应用程序设计因为它与数据库相关-如前面所述，数据库存在于操作系统与数据库应用程序之间。
Route 2: Learn application design as it relates to databases- As I said before, the database sits between the OS and the database 自主节奏的好处更多地来自于学习应用程序如何适应进程(跳过程序中的部分)以及如何使用评估。
Self pacing benefits more often come from how a learning app adapts to progression(skipping sections in 孩子们在城市，城镇，甚至偏僻的地方，手机是更常见的比学校可从学习应用程序像这样的受益。
Children in cities, towns, even remote places where cell phones are more common than schools can benefit from a learning app like this one.
