I
目录
第 1 周 .............................................................................................................................................. 1
1、 引言(Introduction) .................................................................................................... 1
1.1 欢迎............................................................................................................................ 1
1.2 机器学习是什么？ .................................................................................................... 4
1.3 监督学习 .................................................................................................................... 6
1.4 无监督学习 .............................................................................................................. 10
2、 单变量线性回归(Linear Regression with One Variable) ........................................ 15
2.1 模型表示 .................................................................................................................. 15
2.2 代价函数 .................................................................................................................. 17
2.3 代价函数的直观理解 I ............................................................................................ 19
2.4 代价函数的直观理解 II ........................................................................................... 20
2.5 梯度下降 .................................................................................................................. 21
2.6 梯度下降的直观理解 .............................................................................................. 24
2.7 梯度下降的线性回归 .............................................................................................. 27
2.8 接下来的内容 .......................................................................................................... 29
3、 线性代数回顾(Linear Algebra Review) ................................................................... 30
3.1 矩阵和向量 .............................................................................................................. 30
3.2 加法和标量乘法 ...................................................................................................... 31
3.3 矩阵向量乘法 .......................................................................................................... 32
3.4 矩阵乘法 .................................................................................................................. 33
3.5 矩阵乘法的性质 ...................................................................................................... 34
3.6 逆、转置 .................................................................................................................. 35
第 2 周 ............................................................................................................................................ 36
4、 多变量线性回归(Linear Regression with Multiple Variables) ................................ 36
4.1 多维特征 .................................................................................................................. 36
4.2 多变量梯度下降 ...................................................................................................... 37
4.3 梯度下降法实践 1-特征缩放 ................................................................................. 39
4.4 梯度下降法实践 2-学习率 ..................................................................................... 40
4.5 特征和多项式回归 .................................................................................................. 41
4.6 正规方程 .................................................................................................................. 42
4.7 正规方程及不可逆性（选修） .............................................................................. 44
5、 Octave 教程(Octave Tutorial) .................................................................................. 47
5.1 基本操作 .................................................................................................................. 47
5.2 移动数据 .................................................................................................................. 54
5.3 计算数据 .................................................................................................................. 62
5.4 绘图数据 .................................................................................................................. 70
5.5 控制语句：for，while，if 语句 ............................................................................. 76
5.6 向量化 ...................................................................................................................... 82
5.7 工作和提交的编程练习 .......................................................................................... 86
第 3 周 ............................................................................................................................................ 88
6、 逻辑回归(Logistic Regression) ................................................................................ 88
6.1 分类问题 .................................................................................................................. 88
