├── .gitignore ├── Appendix B Linear Algebra.ipynb ├── Appendix C The E-M Algorithm.ipynb ├── Chapter 2 Training vs. Testing.ipynb ├── Learning From Data_A Short Course Notes.ipynb ├── README.md ├── Solutions to Chapter 1 The Learning Problem.ipynb ├── Solutions to Chapter 2 Training versus Testing.ipynb ├── Solutions to Chapter 3 The Linear Model.ipynb ├── Solutions to Chapter 4 Overfitting.ipynb ├── Solutions to Chapter 5 Three Learning Principles.ipynb ├── Solutions to Chapter 6 Similarity-Based Methods.ipynb ├── Solutions to Chapter 7 Neural Networks.ipynb ├── Solutions to Chapter 8 Support Vector Machine.ipynb ├── Solutions to Chapter 9 Learning Aides.ipynb ├── __init__.py ├── data ├── usps.h5 └── usps.h5.zip ├── diff_Qfs_raw.csv ├── diff_sigmas.csv ├── diff_sigmas_raw.csv ├── files ├── LFD7.7_1.jpg ├── LFD7.7_2.jpg └── LFD7.7_3.jpg ├── googlea4c5947d4a6e4a59.html ├── lasso_ivanov_Eout_C ├── lasso_ivanov_all_Eouts.csv ├── libs ├── __init__.py ├── data_util.py ├── linear_models.py ├── nn.py └── plot.py ├── overfit_mean_diff_raw.csv ├── overfit_std_diff_raw.csv ├── ridge_ivanov_Eout_C ├── ridge_ivanov_all_Eouts.csv ├── ridge_tikhonov_Eout_lambda └── ridge_tikhonov_all_Eouts.csv /.gitignore: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/niuers/Learning-From-Data-A-Short-Course/HEAD/.gitignore -------------------------------------------------------------------------------- /Appendix B Linear Algebra.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/niuers/Learning-From-Data-A-Short-Course/HEAD/Appendix B Linear Algebra.ipynb -------------------------------------------------------------------------------- /Appendix C The E-M Algorithm.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/niuers/Learning-From-Data-A-Short-Course/HEAD/Appendix C The E-M 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