WITH NEURAL NETWORKS - 翻译成中文

• 神经网络

在 英语 中使用 With neural networks 的示例及其翻译为 中文

Q: Most of you are familiar with neural networks, but please explain your initial thoughts and how it is formed in your mind.
Q：在座的大多数人对神经网络都很熟悉了首页，但还是请你解释一下最初的想法首页，以及它是如何在你的脑海中形成的。

Data preparation is required when working with neural network and deep learning models.
使用神经网络和深度学习模型时需要准备数据。

And with neural networking and machine learning, there seem to be new algorithms every week, which makes it hard to develop a single architecture.
而神经网络和机器学习，似乎每周都有新的算法，这就很难开发一个单一的架构。

With neural networks on the other hand, this never happens.
神经网络则不然，这种情况永远不会发生。

Deep Image Prior- Image restoration with neural networks but without learning.
No.20Deep-image-prior：使用神经网络进行图像恢复，然而无需学习过程.

Get acquainted with neural networks and Deep Learning to address real-world problems.
学习使用神经网络和深度学习解决现实问题.

Despite the buzz around DeepMind, combining reinforcement learning with neural networks is not new.
尽管围绕DeepMind的喧嚣不断，但结合强化学习和神经网络并非新鲜事。

But what you gain in terms of accuracy with neural networks, you lose in transparency and control.
但神经网络在保证准确性的同时，失去的却是透明度和控制力。

Luckily there are now hundreds open source and proprietary packages which make working with neural networks a lot easier.
幸运的是，现在有数以百计的开源和专有包，使得使用神经网络工作起来简单多了。

If you would like to do some experimenting with neural networks yourself, there is software available to do so.
如果你想自己做一些神经网络的实验，有软件可以帮助你。

If we include deep learning, more than three quarters of the retrieved computer science publications deal with neural networks.
如果将深度学习包括在内，那么检索结果中有四分之三以上涉及神经网络。

They want to do everything with neural networks, and do nothing with anything that looks like classical programming.
他们想用神经网络做任何事情，对任何看起来像经典编程的东西都不做任何事。

It may be that as with neural networks, genetic algorithms can be applied to some portion of the pathfinding problem.
也许在和神经网络结合的情况下，遗传算法可以应用于寻路问题的某个部分。

In fact, I would say that Keras is an essential tool in the toolbox of any data scientist working with neural networks.
事实上，我想说的是，Keras是任何一个使用神经网络的数据科学家的工具。

But it also tackles one of the most common problems with neural networks: the fact that they need huge amounts of data.
最重要的是，它还解决了神经网络最常见的问题之一：需要大量数据才能进行训练。

Jeff Dean from the Google Brain team pointed out that with neural networks, results get better with more data, bigger models, and more computation.
来自GoogleBrain项目团队的杰夫•迪恩指出，神经网络的使用会使结果更好，因为届时将产生更多的数据、更大的模型及更多的计算。

This makes it hard to establish formal performance guarantees with neural network policies.
这使得很难为神经网络建立正式的性能担保政策。

This makes the creation of formal performance guarantees with neural network policies very difficult.
这使得很难为神经网络建立正式的性能担保政策。

It was inspired by traditional text-to-speech structure replacing all the components with neural network.
它是受传统的文本到语音结构的启发，用神经网络代替所有的组件。

Reasoning With Neural Tensor Networks for Knowledge Base Completion.
本文是我关于论文《ReasoningWithNeuralTensorNetworksforKnowledgeBaseCompletion》的学习笔记。