机器学习笔记 Notes about theory of Machine Learning
This is supposed to be a series of Notes about Machine Learning.
Some subjects of these Notes are as follows：
1、base theory of prob and statistics
2、base theory of linear algebra
3、feature engineering in ML
4、optimization method in ML
5、regularization in ML
6、distance metrics in ML
7、effectiveness evaluation in ML
8、common model such as SVM、LR、GBDT、RF etc.
笔记将会包含两部分内容：一部分是以介绍的形式，一部分是以QA的形式。