July 2018
Intermediate to advanced
310 pages
8h 21m
Chinese
Content preview from 深度学习入门 : 基于Python的理论与实现
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3.6 手写数字识别
69
中神经元y
2
颜色最深，输出的值最大。这表明这个神经网络预测的是y
2
对应
的类别，也就是“2”。
图3-23 输出层的神经元对应各个数字
= “
0
”
= “
2
”
= “
1
”
= “
9
”
输入层
输出层
某种运算
y
0
y
1
y
2
y
9
3.6
手写数字识别
介绍完神经网络的结构之后，现在我们来试着解决实际问题。这里我们
来进行手写数字图像的分类。假设学习已经全部结束，我们使用学习到的参
数，先实现神经网络的“推理处理”。这个推理处理也称为神经网络的前向
传播（
forward propagation
）。
和求解机器学习问题的步骤（分成学习和推理两个阶段进行）一样，
使用神经网络解决问题时，也需要首先使用训练数据（学习数据）进
行权重参数的学习；进行推理时，使用刚才学习到的参数，对输入
数据进行分类。
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