|
..
|
|
.ipynb_checkpoints
|
|
CaseStudy_Churn_Analysis_2016.ipynb
|
|
Correlation, supervised segmentation, and tree-structured models.ipynb
|
|
Lecture_Bagging_RandomForests_3.ipynb
|
|
Lecture_BiasVariance_3.ipynb
|
|
Lecture_Binning_NonLinear_3.ipynb
|
|
Lecture_Clustering_3.ipynb
|
|
Lecture_DecisionTrees_3.ipynb
|
|
Lecture_ERM_LogReg_3.ipynb
|
|
Lecture_FeatureSelection_3.ipynb
|
|
Lecture_GradientTreeBoosting_3.ipynb
|
|
Lecture_Metrics_Ranking_3.ipynb
|
|
Lecture_MultiArmedBandit.ipynb
|
|
Lecture_NumPyBasics_3.ipynb
|
|
Lecture_PandasIntro_3.ipynb
|
|
Lecture_PhotoSVD_3.ipynb
|
|
Lecture_Regularization_3.ipynb
|
|
Lecture_Resampling_3.ipynb
|
|
Lecture_SPAM.ipynb
|
|
Lecture_SVM_3.ipynb
|
|
Lecture_SimpleOverfittingExample_3.ipynb
|
|
Lecture_SimpleiPythonExample_3.ipynb
|
|
Lecture_TextMining_3.ipynb
|
|
Lecture_kNN_3.ipynb
|
|
bias_variance.py
|
|
churn_analysis.py
|
|
course_utils.py
|
|
eval_plots.py
|