Neural networks
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英英释义
Neural Networks
Neural Networks is a monthly peer-reviewed scientific journal and an official journal of the International Neural Network Society, European Neural Network Society, and Japanese Neural Network Society. It was established in 1988 and is published by Elsevier.
以上来源于:Wikipedia
权威例句
ImageNet classification with deep convolutional neural networksNeural Networks: A Comprehensive Foundation
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Neural networks and physical systems with emergent collective computational abilities
Neural networks for pattern recognition
Dropout: a simple way to prevent neural networks from overfitting
Recombinant mouse OB protein: evidence for a peripheral signal linking adiposity and central neural networks.
...the Dimensionality of Data with Neural Networks
1. Neural networks are computer systems which mimic the workings of the brain.
神经网络是模仿大脑运行的计算机系统。
《柯林斯英汉双解大词典》
2. Their research thus implies a different character model, which is supposed to manipulate the neural networks inside.
因此，他们的研究暗示了一种不同的特征模型，该模型被认为是用来操纵内部神经网络的。
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3. This is a bit disturbing, because the important habitual neural networks are not formed by mere routine, nor can they be reversed by clever cues.
这有点令人不安，因为重要的习惯神经网络不是仅仅通过例行程序形成的，也不能通过聪明的线索来逆转。
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4. Neural networks have several different topologies, but the simplest is known as a feedforward network.
神经网络有几种不同的拓扑结构，但是最简单的一种是前馈网络。
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5. This sort of learning could take place with neural networks or support vector machines, but another approach is to use decision trees.
这种学习可以使用神经网络或者支持向量机，不过用决策树也可以实现类似的功能。
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6. The RF's neural networks link up with the cerebral cortex, which regulates how we think and remember.
RF的神经网络与调节我们如何去思考与记忆的大脑皮层相连接。
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7. The brain works on neural networks.
大脑依靠神经网络工作。
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8. We have come to literally see how stress and curiosity edits which sensory information is given entry to our neural networks and where the input ends up.
我们现在能看到压力和好奇心如何改变了输入到我们的神经网络里的感觉信息，以及如何影响这些进入的感觉信息最终将被送到那里。
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9. Supervised learning is the most common technique for training neural networks and decision trees.
监督学习是训练神经网络和决策树的最常见技术。
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10. This type of learning could probably be carried out with neural networks, though it is hard to imagine that the problem is simple enough for decision trees.
这种类型的学习通常交给神经网络来完成，虽然很难想象，但用决策树来完成这类问题也很简单。
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11. A new study published July 27 in the journal Nature shows the neural networks in the brains of the middle-aged and elderly have weaker connections and fire less robustly than in youthful ones.
《自然》杂志在7月27日公布的一项研究新成果显示，跟年轻人相比，中老年人大脑神经网络的互相联系和运作强度都更弱一些。
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12. The now-legendary summer workshop at Dartmouth in 1956 birthed automata, the first neural networks and the invention of a program capable of thinking non-numerically.
达特茅斯学院的“现时传奇”夏季研讨会于 1956 年诞生出自动机那是第一个神经网络 还发明了具备非数值思维能力的程序.
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13. That is interesting because it kind of looks to some extent like the way neurons look and this is often known as neural networks.
有趣的是，因为它看上去很像神经元的样子，所以通常都将它称之为神经网络。
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14. In the past two decades researchers have explored several alternative strategies, from neural networks to general rules based on advice from expert players, with indifferent results.
过去的二十年间，研究人员探究了若干种二选一策略，从神经网络到基于优秀选手的建议而建立的法则，但结果仍是一样。
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15. Learning requires the brain to create new neural networks.
学习需要大脑去创造神经网络。
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16. The researchers used a technique called artificial neural networks to look for patterns in the data.
研究人员用所谓的人工神经网络的技术分析数据的模式。
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17. There are many other AI techniques that can be implemented and tried in a Chess program, such as neural networks, genetic algorithms, and collaborative computing.
许多其他的人工智能技术也被应用到这类程序中，例如神经网络，遗传算法和协同计算。
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18. Indeed, the names of major subfields of computer science-such as artificial neural networks, genetic algorithms, and evolutionary computation-attest to the influence of biological analogies.
说实话，在计算机科学的一些主要分支学科的命名上就可以看出生物学的影子，譬如人工神经网络，遗传算法和进化计算法等等。
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19. Crudely put, the brain's neural networks can be thought of as electrical circuits.
平白的说，大脑神经网络可以比作电路。
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20. We now have computer viruses, neural networks, Biosphere 2, gene therapy, and smart CARDS — all humanly constructed artifacts that bind mechanical and biological processes.
而今我们有了电脑病毒，神经网络，生物圈二号，基因治疗法以及智能卡——所有这些人工构造的产品，联接起了机械与生物过程。
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21. Many algorithms are used to create supervised learners, the most common being neural networks, Support Vector Machines (SVMs), and Naive Bayes classifiers.
创建监管学习程序需要使用许多算法，最常见的包括神经网络、SupportVectorMachines (SVMs)和Naive Bayes分类程序。
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22. He has been tweaking his "convolutional neural networks" (ConvNets) ever since.
从那时起，他就一直在调整和改良他的“卷积神经网络”(ConvNets)。
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23. This approach is superior to the apparently "complex" methods such as Bayesian networks or neural networks.
这种方式倾向于 “复杂的”方法，比如Bayesian网络或神经网络。
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24. Techniques such as Bayesian networks or neural networks use highly expressive models, which try to produce a non-biased classifier in order to "describe" a corpus of documents.
Bayesian网络或神经网络等技术使用表达能力非常强的模型，力求生成无偏向的分类器来“描述”文档集。
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25. For estimators these trends mean a more consistent and timely supply of historical data, and they point toward a bright future for Neural Networks.
对评估人员来说，这些趋势意味着他们能够得到更一致和及时的数据，他们将走向神经网络的美好的未来。
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26. Some researchers theorize that the REM, or rapid eye movement, phase of sleep is when the brain produces and consolidates neural networks for memory and cognition.
一些研究人员提出，大脑在快速动眼睡眠期会产生并巩固形成记忆和认知的神经元。
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27. Neural-Networks: This would have been a very simple and straightforward model where the inputs are whatever sensors we give the probes, and the outputs are key-presses.
神经网络：无论什么传感器都会被作为探测输入，输出则是同步按键，这是一个直接并且简单的模型。
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28. It is interesting to note that Neural Networks is an evolution of learning-oriented estimation, in which the method algorithm is trained to behave like a human expert.
有意思的是，神经网络是一种对学习型评估的进化，算法经过训练后其行为就像是一个人类专家。
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29. The neural networks and dynamics associated with general reward and social interactions overlap heavily.
神经网络和动力系统（与一般奖励和社会互动相联系）有很多相互交叠的地方。
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30. This book will teach you many of the core concepts behind neural networks and deep learning.
这本书将告诉你许多神经网络与深度学习后面的核心概念。
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Neural networks
