1. Machine Learning Definition and PLA:
http://www.cnblogs.com/HappyAngel/p/3456762.html
2. Machine learning classification:
http://blog.csdn.net/SteveYinger/article/details/51115731
3. The feasibility of machine learning:
http://blog.csdn.net/steveyinger/article/details/51171828
4. The number of machine learning prediction functions:
http://blog.csdn.net/MajorDong100/article/details/51223794?locationNum=13
5. Noise andError：
http://blog.csdn.net/red_stone1/article/details/71512186
6. Linear regression:
https://www.douban.com/note/323611077/
7. Logistic regression:
https://www.douban.com/note/323644915/
8. Binary classification linear model:
http://blog.csdn.net/red_stone1/article/details/72453273
8. Overfitting:
https://www.douban.com/note/325443925/
9. Regularization:
https://www.douban.com/note/325451389/
10. Verify:
http://blog.csdn.net/red_stone1/article/details/72834968
11. Summary: