忘记1月19日开课了，少上了两节课，要努力补上了，每周3小时的课程还是可以接受的，开个学习笔记记录下学习心得。

00 - 课程与书籍简介

1.课程简介

统计学习（Statistical Learning）

Start：2015.1.19　　End：2015.4.5　　Estimated Effort：3 hours per week

https://class.stanford.edu/courses/HumanitiesandScience/StatLearning/Winter2015/about

2.配套书籍

An Introduction to Statistical Learning with Applications in R

（1）面向统计学家和需要使用统计学习技术的非统计学家，需要具有线性回归（ linear regression）的相关知识，但是不需具备矩阵代数（matrix algebra）的基础。

（2）相关R Code和R Package

R Code：http://www-bcf.usc.edu/~gareth/ISL/code.html

R Package：http://cran.r-project.org/web/packages/ISLR/index.html

（3）数据集Data Sets and Figures
http://www-bcf.usc.edu/~gareth/ISL/data.html

（4）第4版的勘误表
Page 144, Should read "For these data we don‘t expect this to be a problem, since p=3 and n=10,000," since p=3 not 4.
Page 149, (4.23) is missing the -1/2 log|\Sigma_k| term.
Page 211: The equation Cp=sigma hat^2(Cp‘+n) should be Cp=sigma hat^2/n(Cp‘+n)
Page 217, scale invariant should be scale equivariant.
Page 254: The parameter to control the number of folds in cv.glmnet() is "nfolds" not "folds".
Page 260, Exercise 3 and 4: the sum of square terms should be squared.
Page 295: “The generic plot() function recognizes that gam2 is an object of class gam," should read “The generic plot() function recognizes that gam.m3 is an object of class gam,”
Page 318, figure 8.8: the colors for OOB: Bagging and OOB: RandomForest are interchanged in the legend. OOB: RandomForest is lowest.
Page 333, exercise 8 should refer to test MSE rather than test error rate.

Stanford Open Course - Statistical Learning 00