深层神经网络 - 翻译成英语

• deep neural network
• deep neural networks

在 中文 中使用 深层神经网络 的示例及其翻译为 英语

由于深层神经网络的工作方式不透明，这是一个很难回答的问题。
Because of the opaque ways in which deep neural networks work, it's a tricky question to answer.

为了提高深层神经网络的训练效果，人们对神经元的连接方法和激活函数等方面做出相应的调整。
In order to improve the training effect of the deep neural networks, the neuron connection methods and activation functions have been adjusted.

Facebook，百度、亚马逊和其他一些公司正在使用的GPU集群来研究深层神经网络相关的机器学习应用程序。
Facebook, Baidu, Amazon and others are using clusters of GPUs in machine learning applications that come under the aegis of deep neural networks.

到目前为止，我们已经看到了一些深层神经网络的基础知识。
We have seen some of the basics of deep neural networks up to this point.

当你听到深度学习这个词的时候，想想一个巨大的深层神经网络。
When you hear the term deep learning, just think of a large deep neural net.

这种增量过程在简单数据上逐层构建，形成”深层神经网络“的核心。
This sort of incremental process, building bit by bit on simple data, is at the core of a deep neural network.

残差学习最重要的突破在于重构了学习的过程，并重新定向了深层神经网络中的信息流。
Residual learning reformulates the learning procedure and redirects the information flow in deep neural networks.

当你听到“深度学习”这个词时，只要想想一个大的深层神经网络。
When you hear the term deep learning, just think of a large deep neural net.

它们也被称作CNNs或着ConvNets，是深层神经网络领域的主力。
Also called CNNs or ConvNets, these are the workhorse of the deep neural network field.

发表在老年学杂志上的一篇最新论文展示了深层神经网络在评估患者生物学年龄中的应用。
The latest paper published in the Journals of Gerontology demonstrated the application of the deep neural networks to assessing the biological age of the patients.

AlphaGo和AlphaGoZero都采用一种被称之为强化学习的机器学习方法及深层神经网络系统。
Both AlphaGo and AlphaGo Zero use a machine-learning approach known as reinforcement learning as well as deep neural networks.

同时，从Arm到西部数据（WesternDigital）的芯片公司正在研究内核，以加速深层神经网络的推理部分。
Meanwhile, chip companies from ARM to Western Digital are working on cores to accelerate the inference part of deep neural nets.

深层神经网络在经过训练后可以识别被操纵过或复制的图像，而且自2015年以来，神经网络在相似的图像识别任务上的表现优于人类。
Deep neural networks can be trained to identify manipulated or duplicate images, and since 2015, neural networks have been outperforming humans on similar image-recognition tasks.

谷歌宣布推出ContentSafetyAPI，这是个开发者工具包，能利用深层神经网络来处理图片以降低其对互联网用户的曝光度。
Google launched the Content Safety API, which allows developers to use deep neural networks to process images to reduce their exposure to Internet users.

深层神经网络.
Deep Neural Networks.

为何深层神经网络难以理解.
Why deep neural networks are hard to understand.

但是深层神经网络受到严重的限制。
But deep neural networks suffer from severe limitations.

为什么深层神经网络难以训练？★?
Why are deep neural networks hard to train?

深层神经网络对于有监督学习已经非常成功。
Deep neural networks have been very successful for supervised learning.

极深的深层神经网络、自然语言处理及更多.
Very deep neural networks, natural language processing and more.