# 臺灣大學林軒田機器學習筆記
> 貢獻者：[紅色石頭](https://github.com/RedstoneWill)
+ [紅色石頭的機器學習之路](https://redstonewill.github.io/)
+ [紅色石頭的專欄](http://blog.csdn.net/red_stone1)
+ [知乎：紅色石頭](https://www.zhihu.com/people/red_stone_wl)
+ [RedstoneWill 的微博](http://weibo.com/redstonewill)
+ 公眾號：紅色石頭的機器學習之路
+ [課程資源匯總](https://github.com/RedstoneWill/NTU-HsuanTienLin-MachineLearning)
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+ [在線閱讀](https://ntuml.apachecn.org)
+ [PDF格式](https://www.gitbook.com/download/pdf/book/wizardforcel/ntu-hsuantienlin-ml)
+ [EPUB格式](https://www.gitbook.com/download/epub/book/wizardforcel/ntu-hsuantienlin-ml)
+ [MOBI格式](https://www.gitbook.com/download/mobi/book/wizardforcel/ntu-hsuantienlin-ml)
+ [代碼倉庫](https://github.com/apachecn/ntu-hsuantienlin-ml)
- 臺灣大學林軒田機器學習筆記
- 機器學習基石
- 1 -- The Learning Problem
- 2 -- Learning to Answer Yes/No
- 3 -- Types of Learning
- 4 -- Feasibility of Learning
- 5 -- Training versus Testing
- 6 -- Theory of Generalization
- 7 -- The VC Dimension
- 8 -- Noise and Error
- 9 -- Linear Regression
- 10 -- Logistic Regression
- 11 -- Linear Models for Classification
- 12 -- Nonlinear Transformation
- 13 -- Hazard of Overfitting
- 14 -- Regularization
- 15 -- Validation
- 16 -- Three Learning Principles
- 機器學習技法
- 1 -- Linear Support Vector Machine
- 2 -- Dual Support Vector Machine
- 3 -- Kernel Support Vector Machine
- 4 -- Soft-Margin Support Vector Machine
- 5 -- Kernel Logistic Regression
- 6 -- Support Vector Regression
- 7 -- Blending and Bagging
- 8 -- Adaptive Boosting
- 9 -- Decision Tree
- 10 -- Random Forest
- 11 -- Gradient Boosted Decision Tree
- 12 -- Neural Network
- 13 -- Deep Learning
- 14 -- Radial Basis Function Network
- 15 -- Matrix Factorization
- 16（完結） -- Finale