个人学习笔记、资料汇总
Machine Learning(Andrew Ng,Stanford University)
学习笔记
第1~8章笔记：http://www.cnblogs.com/qpswwww/p/8934162.html
第9~12章笔记：http://www.cnblogs.com/qpswwww/p/9291027.html
第13~15章笔记：http://www.cnblogs.com/qpswwww/p/9291626.html
第16~18章笔记：http://www.cnblogs.com/qpswwww/p/9293593.html
作业代码
Exercise 1~2:http://www.cnblogs.com/qpswwww/p/9273830.html
Exercise 3~4:http://www.cnblogs.com/qpswwww/p/9280085.html
Exercise 5~6:http://www.cnblogs.com/qpswwww/p/9281062.html
Exercise 7~8:http://www.cnblogs.com/qpswwww/p/9284646.html
18.06,Linear Algebra(Gilbert Strang,Massachusetts Institute of Technology)
学习笔记
Lecture 1~5:https://www.cnblogs.com/qpswwww/p/8835857.html
Lecture 6~10:https://www.cnblogs.com/qpswwww/p/8910535.html
Lecture 11~15:https://www.cnblogs.com/qpswwww/p/9000256.html
Lecture 16~20:https://www.cnblogs.com/qpswwww/p/9053980.html
Lecture 21~25:https://www.cnblogs.com/qpswwww/p/9069968.html
Lecture 26~30:https://www.cnblogs.com/qpswwww/p/9301602.html
Lecture 31~35:https://www.cnblogs.com/qpswwww/p/9306848.html
CS229,Machine Learning(Andrew Ng,Stanford University)
学习笔记
Note 1(最小二乘法、局部加权线性回归、极大似然估计、牛顿法)
https://www.cnblogs.com/qpswwww/p/9298394.html
Note 2(广义线性模型、高斯判别分析模型、朴素贝叶斯)
https://www.cnblogs.com/qpswwww/p/9308786.html
Note 3(支持向量机、SMO算法)
https://www.cnblogs.com/qpswwww/p/9316658.html
Note 4(学习理论)
https://www.cnblogs.com/qpswwww/p/9316666.html
Note 5(正则化与模型选择)
https://www.cnblogs.com/qpswwww/p/9319773.html
Note 6(感知机与大间隔分类器、在线学习)
https://www.cnblogs.com/qpswwww/p/9323405.html
Note 7(K-means聚类、高斯混合模型、EM算法)
https://www.cnblogs.com/qpswwww/p/9324820.html
Note 8(EM算法)
https://www.cnblogs.com/qpswwww/p/9325726.html
Note 9(因子分析)
https://www.cnblogs.com/qpswwww/p/9328974.html
Note 10(主成分分析PCA)
https://www.cnblogs.com/qpswwww/p/9332522.html
Note 11(独立成分分析ICA)
https://www.cnblogs.com/qpswwww/p/9334358.html
Note 12(强化学习与自适应控制)
https://www.cnblogs.com/qpswwww/p/9337740.html
作业代码
Problem Set 1
https://www.cnblogs.com/qpswwww/p/9340296.html
Problem Set 2
https://www.cnblogs.com/qpswwww/p/9343381.html
Machine Learning Foundations(Hsuan-Tien Lin,National Taiwan University)
学习笔记
Lecture 2 & Lecture 3
https://www.cnblogs.com/qpswwww/p/9346790.html
Lecture 4 & Lecture 5
https://www.cnblogs.com/qpswwww/p/9349371.html
Lecture 6 & Lecture 7
https://www.cnblogs.com/qpswwww/p/9351187.html
Lecture 8 & Lecture 9
https://www.cnblogs.com/qpswwww/p/9355221.html
Lecture 10 & Lecture 11
https://www.cnblogs.com/qpswwww/p/9360160.html
Lecture 12 & Lecture 13
https://www.cnblogs.com/qpswwww/p/9362409.html
Lecture 14 & Lecture 15
https://www.cnblogs.com/qpswwww/p/9366442.html
Lecture 16
https://www.cnblogs.com/qpswwww/p/9370593.html
Machine Learning Techniques(Hsuan-Tien Lin,National Taiwan University)
Lecture 1 & Lecture 2
https://www.cnblogs.com/qpswwww/p/9372106.html
Lecture 3 & Lecture 4
https://www.cnblogs.com/qpswwww/p/9377102.html
Lecture 5 & Lecture 6
https://www.cnblogs.com/qpswwww/p/9379510.html
Lecture 7 & Lecture 8
https://www.cnblogs.com/qpswwww/p/9382439.html
Lecture 9 & Lecture 10
https://www.cnblogs.com/qpswwww/p/9384671.html
Lecture 11 & Lecture 12
https://www.cnblogs.com/qpswwww/p/9389574.html
Lecture 13 & Lecture 14
https://www.cnblogs.com/qpswwww/p/9392382.html
