斯坦福大学机器学习课程个人学习笔记（上）
........................................\(1)线性回归、logistic回归和一般回归.pdf
........................................\(2)判别模型、生成模型与朴素贝叶斯方法.pdf
........................................\(3)支持向量机SVM（上）.pdf
........................................\(4)支持向量机SVM（下）.pdf
........................................\(5)规则化和模型选择.pdf
........................................\(6)K-means聚类算法.pdf
........................................\(7)混合高斯模型和EM算法.pdf
........................................\(8)EM算法.pdf
........................................\请先查看该说明.txt
斯坦福大学机器学习课程个人学习笔记（下）
........................................\(10)主成分分析.pdf
........................................\(11)独立成分分析.pdf
........................................\(12)线性判别分析.pdf
........................................\(13)因子分析.pdf
........................................\(14)增强学习.pdf
........................................\(15)典型关联分析.pdf
........................................\(16)偏最小二乘法回归.pdf
........................................\(9)在线学习.pdf
........................................\请先查看该说明.txt