What is the translation of " 将神经网络 " in English?

• neural networks
• neural network

Examples of using 将神经网络 in Chinese and their translations into English

SyntaxNet将神经网络运用于歧义问题。
SyntaxNet applies neural networks to the problem of ambiguity.

霍华德将神经网络描述为“无限灵活的函数”。
Howard describes neural networks as an“infinitely flexible function.”.

SyntaxNet将神经网络运用于歧义问题。
SyntaxNet applies neural networks to the ambiguity problem.

这也是第一次将深层神经网络与强化学习相结合的成功的尝试之一（这篇文章是DeepMind的原文）。
This was one of the first successful attempts at combining deep neural networks with reinforcement learning(this was Deepmind's original paper).

可以将循环神经网络视为同一网络的多个副本，每个副本都将消息传递给后继者。
A recurrent neural network can be thought of as multiple copies of the same network, each passing a message to a successor.

这些传感器将神经网络和机器学习技术相结合，能够给你的面部建立一个部数学模型。
The sensors, combined with neural networks and machine learning techniques, help to make a mathematical model of your face.

CNTK是一个统一的计算网络框架，它将深层神经网络描述为一系列通过有向图的计算步骤。
CNTK is a unified computational network framework that describes deep neural networks as a series of computational steps via a directed graph.

如果某个应用存在这方面的问题，那么将神经网络从云端转移到边缘是可以行得通的。
If an application has concerns in this area, then it may make sense to bring the neural network from the cloud to the edge.

然后，他们将神经网络放在数据上，使其慢慢识别模式。
Then, they turned the neural network loose on the data, leaving it to slowly identify patterns.

然后，他们将神经网络放在数据上，使其慢慢识别模式。
And then the neural networks fed the data, allowing it to slowly identify patterns.

在上个世纪九十年代，Bengio提出将神经网络与序列的概率建模相结合，例如隐马尔可夫模型这种序列的概率建模方法。
In the 1990s, Bengio combined neural networks with probabilistic models of sequences, such as hidden Markov models.

它的使命是将深度神经网络和深度强化学习结合在一起，用于商业环境。
Its mission is to bring deep neural networks and deep reinforcement learning together for business environments.

DeepStack的扑克游戏系统将神经网络与反事实后悔最小化和启发式搜索相结合。
DeepStack's poker playing system combines neural networks with counterfactual regret minimization and heuristic search.

该工具允许你在不编写代码的情况下使用文本快速将神经网络应用于问题。
The tool allows you to quickly apply neural networks to the problem using text, without writing code.

序列的概率模型（Probabilisticmodelsofsequences）：在20世纪90年代，Bengio将神经网络与序列的概率模型相结合，例如隐马尔可夫模型。
Probabilistic models of sequences: In the 1990s, Bengio combined neural networks with probabilistic models of sequences, such as hidden Markov models.

Hinton发起的向量学院（VectorInstitute）的首批项目之一，便是将神经网络连接到多伦多医院提供的大量数据。
One of Vector's first projects, initiated by Hinton, will be connecting neural networks to the huge pools of data available at Toronto hospitals.

在过去的几年中，存储，数据和计算资源的可用性和可承受性将神经网络推向了AI创新的前沿。
In recent years, the availability and affordability of storage, data and computing resources has brought neural networks to the forefront of AI innovation.

这个过程包括使用生成对抗网络(GAN)，这是一种人工智能技术，将神经网络相互对立以创建新的数据。
The process involves using generative adversarial networks(GAN), an AI technique that pits neural networks against each other to create new data.

正如他们将在接下来的会议中讨论的那样，宝马正在将神经网络用于生产线上的车辆检测。
As they will discuss in their upcoming session, BMW is putting neural networks to work inspecting vehicles on the production line.

在过去的几年中，存储，数据和计算资源的可用性和可承受性将神经网络推向了AI创新的前沿。
In the past few years, the availability and affordability of storage, data, and computing resources have pushed neural networks to the forefront of AI innovation.

该工具允许你在不编写代码的情况下使用文本快速将神经网络应用于问题。
This tool allows you to use text quickly to apply neural networks to problems without writing code.

深度强化学习是深度学习与强化学习的融合，是将深度神经网络整合到强化学习框架当中。
Deep reinforcement learning is a fusion of deep learning and reinforcement learning, which integrates deep neural networks into the framework of reinforcement learning.

TensorFlow简化了将神经网络分配到多台计算机的任务，从而可将它们变成一个巨大的脑。
TensorFlow simplifies the distribution of a neural network in a cluster of computers, turning them into one big brain.

卷积层试图将神经网络中的每一小块进行更加深入地分析从而得到抽象程度更高的特征。
The convolution layer tries to analyze each small patch of the neural network in depth, resulting in a higher abstraction feature representation.

理论上讲，我们可以将这些神经网络得到的特征交给语言学家，这样他们就可以为自己打开一片新视野了。
Theoretically, we can pass the features gotten from the neural networks on to the linguists, so that they open brave new horizons for themselves.

我们将训练神经网络，以便在提供一组新数据时可以预测出正确的输出值。
We are going to train the neural network such that it can predict the correct output value when provided with a new set of data.

将神经网络中的每个神经元视为一个简单的统计模型：它接受一些输入，并且传递一些输出。
Think of every neuron in the network below as a simple statistical model: it takes in some inputs, and it passes along some output.

我经常会看到人们将神经网络称为“另一个机器学习工具箱中的工具”。
I sometimes see people refer to neural networks as just“another tool in your machine learning toolbox”.

在DeepQ中，他们将深度神经网络与“强化学习”相结合，强化学习是所有动物都用到的、通过大脑中多巴胺驱动的奖励系统进行学习的方法。
In DeepQ they combined deep neural networks with“reinforcement-learning”, which is the way that all animals learn, via the brain's dopamine-driven reward system.

取得这一成功意味着尽管人工智能是一个复杂的产物，但将神经网络的工作转化为人类所理解的东西并非是不可能的事情。
The success is a sign that, for all its complexity, translating a neural network's work into something a human understands isn't impossible.