October 2020
Intermediate to advanced
693 pages
16h 26m
Chinese
Content preview from 机器学习实战：基于Scikit-Learn、Keras 和TensorFlow （原书第2 版）
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28
｜
第
1
章
统计数据，将数据并入表格，按照人均 GDP 排序，你会得到如表 1-1 所示的摘要。
特征 1
特征 2
新实例
模型
图 1-16：基于模型的学习
表 1-1：金钱能让人更快乐吗？
国家 人均 GDP（美元） 生活满意度
匈牙利 12 240 4.9
韩国 27 195 5.8
法国 37 675 6.5
澳大利亚 50 962 7.3
美国 55 805 7.2
让我们绘制这些国家的数据（见图 1-17）。
匈牙利
韩国
法国
澳大利亚
美国
人均 GDP
（
美元
）
生活满意度
图 1-17：趋势图
这里似乎有一个趋势！虽然数据包含噪声（即部分随机），但是仍然可以看出随着该国人
均 GDP 的增加，生活满意度或多或少呈线性上升的趋势。所以你可以把生活满意度建
模成一个关于人均 GDP 的线性函数。这个过程叫作模型选择。你为生活满意度选择了
一个线性模型，该模型只有一个属性，就是人均 GDP（见公式 1-1）。
机器学习概览
｜
29
公式 1-1：一个简单的线性模型
生活满意度 =
θ
0
+
θ
1
× 人均 GDP
这个模型有两个模型参数：
θ
0
和
θ
1
注 5
。通过调整这两个参数，可以用这个模型来代表任
意线性函数，如图 1-18 所示。
1
人均 GDP
（
美元
）
生活满意度
图 1-18：一些可能的线性模型
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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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.