在神经网络 in English translation

• in neural networks

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

他在神经网络方面的工作推动了支撑Android移动操作系统语音识别的图像识别系统的开发。
His work on neural networks helped lead to the creation of an image-identification system that underpins the Android mobile operating system's speech recognition.

点击按钮后，App冻结几秒钟，同时在每个神经网络上执行100个独立的推断。
After you tap the button the app freezes up for a few seconds while it performs 100 separate predictions on each of the neural networks.

相反，在神经网络中，我们不会告诉计算机如何解决我们的问题。
By contrast, in a neural network we don't tell the computer how to solve our problem.

正则（Regularization）：我们可以在神经网络中边的权重上加一些正则。
Regularization: we can add rules to the weights within the neural network.

在神经网络的许多创新中，计算机和软件在成功的项目中发挥了巨大的作用。
For much of the innovations surrounding neural networks, computers and software have played massive roles in successful projects.

注意，术语“反向传播”在神经网络计算的文献中，用于指代许多不同的事物。
It should be noted that the term backpropagation is used in the neural computing literature to mean a variety of different things.

例如，您可以修剪决策树，在神经网络上使用dropout，或者在回归中向代价函数添加一个惩罚参数。
For example, you could prune a decision tree, use dropout on a neural network, or add a penalty parameter to the cost function in regression.

在训练神经网络时，必须评估网络输出的正确性。
Cost Function When training a neural network, the correctness of the network's output must be assessed.

请注意，它是在训练神经网络时的go-to算法，它是深度学习中最常见的梯度下降类型。
This is the go-to algorithm when training a neural network and it is the most common type of gradient descent within deep learning.

在神经网络知道它要寻找什么样的模式后，研究人员将其释放到开普勒670的较弱信号上。
After the neural network knew what patterns it was looking for, the researchers turned it loose on 670 of Kepler's weaker signals.

相反，在神经网络中，我们不会告诉计算机如何解决我们的问题。
But in a neural network, we don't tell the computer how to solve our problem.

在神经网络中，最小化非凸误差函数的另一个关键挑战是避免陷于多个其他局部最小值中。
Another key challenge of minimizing highly non-convex error functions common for neural networks is avoiding getting trapped in their numerous suboptimal local minima.

知识存储在神经网络中，但解释机制并不容易。
The knowledge is stored in the neural network, but it is not easy to explain the mechanics.

随着数据在神经网络中从一层流向下一层，数据在每层都会以某种方式被转换。
As data flows from one layer to the next in a neural network, each layer transforms the data somehow.

所以在这个问题上得关键点是:我们如何在神经网络中建立这些层次关系?
So at this point the question is: how do we model these hierarchical relationships inside of a neural network?

这种GPU架构在有大量并行化的应用中工作得很好，例如在神经网络中的矩阵乘法。
This GPU architecture works well on applications with massive parallelism, such as matrix multiplication in a neural network.

对学习出来的模型，调整分类器的参数，如在神经网络中选择隐藏单元数。
A set of examples used to tune the parameters of a classifier, for example to choose the number of hidden units in a neural network.

这就是为什么很多人不愿意把赌注押在神经网络的不确定性上。
This is why so many are reluctant to gamble on the mysteries of neural networks.

然后神经网络，是说你想要让机器在神经网络中学习。
Then the neural network means that you want the machine to learn in the neural network.

换句话说，这个规则能用在神经网络的学习中。
In other words, this is a rule which can be used to learn in a neural network.