Introduction to Probability and Statistics for Engineers and Scientists（中文版）
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书籍
动手学深度学习
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Stabel Diffusion 提示词手册
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16
Machine learning and big data
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译者序
序言
1
统计学简介
2
描述统计
3
概率论基础
4
随机变量和期望
5
特殊的随机变量
6
抽样分布
7
参数估计
8
假设检验
9
回归
10
方差分析
11
拟合优度检验和分类数据分析
12
非参数假设检验
13
Quality control
14
Life testing
15
Simulation, bootstrap statistical methods, and permutation tests
16
Machine learning and big data
17
测试脚本
References
附录
A
表格
目录
16.1
Introduction
16.2
Late flight probabilities
16.3
The naive Bayes approach
16.4
Distance-based estimators.The
\(k\)
-nearest neighbors rule
16.5
Assessing the approaches
16.6
When characterizing vectors are quantitative
16.7
Choosing the best probability: a bandit problem
16.8
Problems
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16
Machine learning and big data
16.1
Introduction
16.2
Late flight probabilities
16.3
The naive Bayes approach
16.4
Distance-based estimators.The
\(k\)
-nearest neighbors rule
16.5
Assessing the approaches
16.6
When characterizing vectors are quantitative
16.7
Choosing the best probability: a bandit problem
16.8
Problems
15
Simulation, bootstrap statistical methods, and permutation tests
17
测试脚本