Examples of using Deep learning applications in English and their translations into Chinese
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This week MapR announced a new solution called Quick Start Solution(QSS), focusing on deep learning applications.
近日MapR宣布推出了一款名为QuickStartSolution（QSS）的新解决方案，专注于深度学习应用。Deep learning applications are used in industries from automated driving to medical devices.
从自动驾驶到医疗设备的各种行业使用了深度学习应用程序。Ai and Keras are two off-the-shelf libraries that you can use to quickly develop deep learning applications.
Ai和Keras就是两个现成的库，可用于快速开发深度学习应用程序。For example, home help devices that respond to the voice and know their preferences are based on deep learning applications.
例如，响应您的语音并了解您的偏好的家庭助理设备，即是装载了基于深度学习的应用程序。By leveraging distributed networks, deep learning on the cloud allows you to design, develop and train deep learning applications faster.
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。Early players like Theano and Torch have powered many deep learning applications, but the creators in 2017 announced that they would stop developing the frameworks.
Theano和Torch这类早期框架为许多深度学习应用程序提供了支持，但其创建者在2017年宣布，他们将不再继续开发这些框架。Scientists have been investigating various techniques to reduce the cost and time associated with machine and deep learning application.
科学家们一直在研究各种技术，想要降低机器和深度学习应用方面的时间和资金成本。ReadToMe is another deep learning application that is able to read books to kids by just showing a page you want it to read.
ReadToMe是另一个深度学习应用程序，它可以通过显示你想让孩子阅读的页面来为孩子阅读书籍。For example, a deep learning application using this flexible computing solution could reduce energy consumption by 15%, according to our preliminary experiment.
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。Moreover, we discussed deep learning application and got the reason why Deep Learning. .
此外，我们还讨论了深度学习的应用，并找出了为什么进行深度学习的原因。Deep learning applications in recommendation system.
深度学习在推荐系统中的应用.Deep learning applications in recommendation system.
S- There will be new deep learning applications.
分37秒：将会出现新的深度学习应用。This design makes TensorFlow efficient for deep learning applications.
这种设计使TensorFlow能高效处理深度学习应用。TensorFlow is designed to work effectively for deep learning applications.
这种设计使TensorFlow能高效处理深度学习应用。Trust is a key factor in the implementation of deep learning applications.
信任是实现深度学习应用程序的关键因素。Libdeep is a C library which can be used in deep learning applications.
Libdeep是一个可以用于深度学习应用程序的C库。Several companies have recently unveiled specialized silicon that outperforms GPUs for deep learning applications.
Therefore, in 2017 we will see many new deep learning applications that could significantly impact our lives.
因此，2017年我们将会看到许多影响我们生活的新型深度学习We start with a review of Deep Learning applications and a recap of Machine Learning tools and techniques.
它将首先回顾深度学习应用以及机器学习工具和技术的概述。
