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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第 6章 与学习相关的技巧
188
图6-19 图中的实线是使用了Batch Norm 时的结果，虚线是没有使用Batch Norm 时
的结果：图的标题处标明了权重初始值的标准差
w:1.0 w:0.541169526546 w:0.292864456463 w:0.158483319246
w:0.0125935639088w:0.0251188643151w:0.0464158883361w:0.0857695898591
w:0.00116591440118w:0.00215443469003w:0.00398107170553w:0.0073564225446
w:0.0001w:0.000184784979742w:0.000341454887383w:0.00063095734448
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正则化
机器学习的问题中，过拟合是一个很常见的问题。过拟合指的是只能拟
合训练数据，但不能很好地拟合不包含在训练数据中的其他数据的状态。机
器学习的目标是提高泛化能力，即便是没有包含在训练数据里的未观测数据，
也希望模型可以进行正确的识别。我们可以制作复杂的 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.