Examples of using Hidden layer in English and their translations into Chinese
{-}
-
Political
-
Ecclesiastic
-
Programming
In other words, a single hidden layer is powerful enough to learn any function.
换句话说，一层隐含层就强大到可以学习任何函数了。In other words, a single hidden layer is powerful enough to learn any function.
换言之，一个单一的隐式层已经足够强大到学习任何函数。(Because of this, the hidden layer is also called feature detector.).
也因此，隐式层也称为特征探测器）。Another explanation component could from training neural network to associate semantic attributes with hidden layer nodes- which could boost learning of explainable features.
另一个解释组件可以从训练神经网络关联带有隐藏层节点的语义属性--这可以促进对可解释功能的学习。They are also called deep networks, multi-layer Perceptron(MLP), or simply neural networks and the vanilla architecture with a single hidden layer is illustrated.
该网络也可被称为深度网络、多层感知机（MLP）或简单神经网络，并且阐明了具有单一隐含层的原始架构。In deep neural networks, we have a large number of hidden layers.
在深度神经网络中，我们有大量的隐含层。Deep neural networks- there are neural networks with multiple hidden layers.
深度神经网络--有着多层隐藏层的神经网络。Hidden Layers(There can be more than one hidden layers which are used for processing the inputs received from the input layers). .
Networks with this kind of many-layer structure- two or more hidden layers- are called deep neural networks.
包含这种多层结构（两层或更多隐含层）的网络叫做深度神经网络（deepneuralnetworks）。A deep neural network might have 10 to 20 hidden layers, whereas a typical neural network may have only a few.
深层神经网络可能有10到20个隐藏层，而典型的神经网络可能只有少数几个。Now, if we add multiple hidden layers to this MLP, we would also call the network“deep.”.
现在，如果我们向这个MLP添加多个隐藏层，我们也会把网络称为“深度”。A deep neural network might have 10 to 20 hidden layers, whereas a typical neural network may have only a few.
一个深度神经网络可能有10到20个隐含层，而一个典型的神经网络可能只有几层。A Multi Layer Perceptron(MLP) contains one or more hidden layers(apart from one input and one output layer). .
多层感知器（MLP）包含一个或多个隐藏层（除了一个输入层和一个输出层）。Deep learning has come to designate any learning method that can train a system with more than 2 or 3 non-linear hidden layers.
深度学习指的是，任何可以训练多于两到三个非线性隐含层模型的学习算法。The hidden layers between the input and output of a deep neutral network make it impenetrable, even for its developers.
深度中性网络的输入和输出之间的隐藏层使其难以穿透，即使对于其开发人员也是如此。In a Feed-Forward neural network, the information only moves in one direction, from the input layer, through the hidden layers, to the output layer. .
在前馈神经网络中，信息只从一个方向移动，从输入层，通过隐藏层到输出层。In Multilayer Perceptron with Two Hidden Layers, you have two input neurons, two hidden layers and four nodes and then the output comes.
在两个隐藏层的多层感知机中，有两个输入神经元、两个隐藏层和四个节点，然后给出输出。Neural networks and deep learning have many inputs that go through several hidden layers before resulting in one or more outputs.
神经网络和深度学习有许多输入，它们经过几个隐藏层后才产生一个或多个输出。Understanding what Hidden Layers Do: The bulk of the knowledge in a deep learning model is formed in the hidden layers.
理解隐藏层做了什么：深度学习模型中的大部分知识是在隐藏层中形成的。Combining big data with large amounts of compute makes it possible to create artificial neural networks with many so-called hidden layers.
将大数据与大量计算相结合，可以创建具有许多所谓的隐藏层的人工神经网络。
