目录1

目录2
1 Introduction 1
2 Overview of Supervised Learning 9
3 Linear Methods for Regression 43
4 Linear Methods for Classification 101
5 Basis Expansions and Regularization 139
6 Kernel Smoothing Methods 191
7 Model Assessment and Selection 219
8 Model Inference and Averaging 261
9 Additive Models, Trees, and Related Methods 295
10 Boosting and Additive Trees 337
11 Neural Networks 389
12 Support Vector Machines and Flexible Discriminants 417
13 Prototype Methods and Nearest-Neighbors 459
14 Unsupervised Learning 485
15 Random Forests 587
16 Ensemble Learning 60
17 Undirected Graphical Models 625
18 High-Dimensional Problems: p ≫ N 649


目录3

都是好书，学习了

所有专题索引：
01.数据挖掘专题：https://bbs.pinggu.org/thread-2161511-1-1.html
02.机器学习专题：https://bbs.pinggu.org/thread-3702096-1-1.html
03.Hadoop大数据平台专题：https://bbs.pinggu.org/thread-2515116-1-1.html
04.Spark大数据平台专题：https://bbs.pinggu.org/thread-3702039-1-1.html
05.算法专题(CLRS, DPV, KT, SW 4合1)：

所有专题索引：
01.数据挖掘专题：https://bbs.pinggu.org/thread-2161511-1-1.html
02.机器学习专题：https://bbs.pinggu.org/thread-3702096-1-1.html
03.Hadoop大数据平台专题：https://bbs.pinggu.org/thread-2515116-1-1.html
04.Spark大数据平台专题：https://bbs.pinggu.org/thread-3702039-1-1.html
05.算法专题(CLRS, DPV, KT, SW 4合1)：https://bbs.pinggu.org/thread-4621817-1-1.html