├── Exercises ├── Chapter 10 │ ├── ch10_applied_exercises.ipynb │ └── ch10_exercises.md ├── Chapter 12 │ ├── ch12_applied_exercises.ipynb │ └── ch12_exercises.md ├── Chapter 3 │ ├── ch3_applied_exercises.ipynb │ └── ch3_exercises.md ├── Chapter 4 │ ├── ch4_applied_exercises.ipynb │ └── ch4_exercises.md ├── Chapter 5 │ ├── ch5_applied_exercises.ipynb │ └── ch5_exercises.md ├── Chapter 6 │ ├── ch6_applied_exercises.ipynb │ └── ch6_exercises.md ├── Chapter 7 │ ├── ch7_applied_exercises.ipynb │ └── ch7_exercises.md ├── Chapter 8 │ ├── ch8_applied_exercises.ipynb │ └── ch8_exercises.md └── Chapter 9 │ ├── ch9_applied_exercises.ipynb │ └── ch9_exercises.md ├── LICENSE ├── Notebooks ├── Lab_03.6_Linear_Regression.ipynb ├── Lab_04.7_Classification_Methods.ipynb ├── Lab_05.3_Cross_Validation_and_the_Bootstrap.ipynb ├── Lab_06.5.1_Subset_Selection.ipynb ├── Lab_06.5.2_Ridge_Regression_and_the_Lasso.ipynb ├── Lab_06.5.3_PCR_and_PLS_Regression.ipynb ├── Lab_07.8_Non_Linear_Modeling.ipynb ├── Lab_08.3_Decision_Trees.ipynb ├── Lab_09.6_Support_Vector_Machines.ipynb ├── Lab_10.9.1_A_Single_Layer_Network_on_the_Hitters_Data.ipynb ├── Lab_10.9.2_A_Multilayer_Network_on_the_MNIST_Digit_Data.ipynb ├── Lab_10.9.3_Convolutional_Neural_Networks.ipynb ├── Lab_10.9.4_Using_Pretrained_CNN_Models.ipynb ├── Lab_10.9.5_IMDb_Document_Classification.ipynb ├── Lab_10.9.6_Recurrent_Neural_Networks.ipynb ├── Lab_11.8_Survival_Analysis.ipynb └── Lab_12.5_Unsupervised_Learning.ipynb ├── README.md ├── data ├── Advertising.csv ├── Auto.csv ├── Auto.data ├── Bikeshare.csv ├── Boston.csv ├── BrainCancer.csv ├── Caravan.csv ├── Carseats.csv ├── Ch12Ex13.csv ├── College.csv ├── Credit.csv ├── Default.csv ├── Fund.csv ├── Heart.csv ├── Hitters.csv ├── Income1.csv ├── Income2.csv ├── Khan_xtest.csv ├── Khan_xtrain.csv ├── Khan_ytest.csv ├── Khan_ytrain.csv ├── NCI60.csv ├── OJ.csv ├── Portfolio.csv ├── Publication.csv ├── Smarket.csv ├── USArrests.csv ├── Wage.csv └── Weekly.csv └── figures ├── 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