工业人工智能概论

第 1 章 绪论·····················································································1
1.1 人工智能的内涵及发展····································································1
1.2 工业人工智能的内涵及发展······························································4
1.2.1 工业人工智能的发展背景 ·····························································4
1.2.2 工业人工智能的发展历程 ·····························································6
1.2.3 工业人工智能与传统人工智能的区别················································7
1.3 工业人工智能的算法功能和典型应用··················································8
1.4 工业人工智能的知识体系································································11
1.5 工业人工智能的关键技术································································12
第 2 章 数据分析与数据挖掘工具··························································14
2.1 工业大数据的特点··········································································15
2.2 工业大数据挖掘的定义及过程···························································17
2.3 工业数据的特征分析·······································································18
2.3.1 工业数据的统计描述 ···································································18
2.3.2 工业数据的相关性分析 ································································20
2.4 工业数据的预处理··········································································23
2.4.1 异常值处理 ···············································································23
工业数据异常值的处理案例 ·····························································25
2.4.2 缺失值处理 ···············································································26
工业数据缺失值的处理案例 ·····························································27
2.4.3 数据归一化处理 ·········································································28
2.4.4 不等时距数据处理 ······································································28
工业数据不等时距处理案例·····························································.29
2.4.5 离群点检测···············································································.32
2.4.6 不平衡数据集检测······································································.34
2.4.7 数据降维处理············································································.36
2.5 假设检验····················································································.41
2.5.1 假设检验的基本原理···································································.41
2.5.2 假设检验的一般步骤···································································.42
2.5.3 假设检验的种类·········································································.42
2.6 多变量分析模型 ··········································································.44
2.6.1 线性模型··················································································.44
2.6.2 广义线性模型············································································.45
2.6.3 线性混合效应模型······································································.47
2.7 *大似然估计··············································································.48
2.8 关联分析····················································································.49
2.8.1 关联规则挖掘···········································································.·51
2.8.2 关联规则算法···········································································.·52
2.8.3 时序关联规则算法······································································.54
2.8.4 一维时序关联规则······································································.56
2.8.5 多维时序关联规则······················································.··············.59
2.9 数据分析系统的体系架构 ··············································.··············.64
第 3 章 机器学习 ····························································.···············.65
3.1 人类的思考过程与机器学习的过程 ···················································.65
3.2 机器学习的知识体系 ···················································.················.67
3.3 Python 语言的优势·········································································.68
3.4 工业人工智能的有监督学习算法 ·······················································.68
3.4.1 决策树算法···············