2018
1. Introduction
2.The PAC Learning Framework
3.Rademacher Complexity and VC-Dimension
4.Model Selection
5.Support Vector Machines
6.Kernel Methods
7.Boosting
8.On-Line Learning
1. Introduction
p 1, include -overview some key learning task , applicatio , basic definition , terminology
1.1 What is ML ?
2.The PAC Learning Framework
3.Rademacher Complexity and VC-Dimension
4.Model Selection
5.Support Vector Machines
6.Kernel Methods
7.Boosting
8.On-Line Learning