什么是神经网络？Um, What Is a Neural Network?
It’s a technique for building a computer program that learns from data. It is based very loosely on how we think the human brain works. First, a collection of software “neurons” are created and connected together, allowing them to send messages to each other. Next, the network is asked to solve a problem, which it attempts to do over and over, each time strengthening the connections that lead to success and diminishing those that lead to failure. For a more detailed introduction to neural networks, Michael Nielsen’s Neural Networks and Deep Learning is a good place to start. For a more technical overview, try Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville.
这是一种建立计算机程序的技术，可以从数据中学习。它非常松散地基于我们认为的人类大脑的工作方式。首先，一组软件 "神经元 "被创建并连接在一起，使它们能够相互发送信息。接下来，该网络被要求解决一个问题，它反复尝试，每次都会加强导致成功的连接，减少导致失败的连接。对于神经网络的更详细介绍，迈克尔-尼尔森的《神经网络和深度学习》是一个好的开始。如果想了解更多的技术概况，可以试试伊恩-古德费洛、约书亚-本吉奥和阿伦-库维尔的《深度学习》。
这些颜色分别代表了什么？What Do All the Colors Mean?
Orange and blue are used throughout the visualization in slightly different ways, but in general orange shows negative values while blue shows positive values.
橙色和蓝色在整个可视化中的使用方式略有不同，但一般来说，橙色显示负值，而蓝色显示正值。
The data points (represented by small circles) are initially colored orange or blue, which correspond to positive one and negative one.
数据点（用小圆圈表示）最初被染成橙色或蓝色，分别对应于正一和负一。
In the hidden layers, the lines are colored by the weights of the connections between neurons. Blue shows a positive weight, which means the network is using that output of the neuron as given. An orange line shows that the network is assiging a negative weight.
在隐蔽层中，线条是由神经元之间的连接权重来着色的。蓝色表示一个正的权重，这意味着网络正在使用神经元的输出作为给定。橙色的线表示网络正在分配一个负的权重。
In the output layer, the dots are colored orange or blue depending on their original values. The background color shows what the network is predicting for a particular area. The intensity of the color shows how confident that prediction is.
在输出层，点的颜色是橙色或蓝色，取决于它们的原始值。背景颜色显示网络对某一特定区域的预测。颜色的强度显示了该预测的自信程度。