├── .gitignore ├── README.md ├── code ├── 00_python_beginner_workshop.py ├── 00_python_intermediate_workshop.py ├── 02_command_line.md ├── 03_file_reading.py ├── 03_python_homework_chipotle.py ├── 04_pandas.py ├── 05_pandas_homework_imdb.py ├── 05_pandas_visualization.py ├── 06_human_learning_iris.py ├── 07_api.py ├── 07_web_scraping.py ├── 08_bias_variance_nb.py ├── 08_knn_sklearn_nb.py ├── 09_glass_id.py ├── 09_model_evaluation_nb.py ├── 10_linear_regression_nb.py ├── 10_yelp_reviews.py ├── 11_logistic_regression_nb.py ├── 11_titanic.py ├── 12_advanced_model_evaluation_nb.py ├── 14_naive_bayes.py ├── 14_yelp_text.py ├── 15_cross_validation_nb.py ├── 15_natural_language_processing_nb.py ├── 16_kaggle.py ├── 16_kaggle_minimal.py ├── 17_decision_trees_nb.py ├── 18_ensembling_nb.py ├── 19_advanced_sklearn.py ├── 19_clustering.py └── 19_grid_exercise.py ├── data ├── airlines.csv ├── beer.txt ├── chipotle.tsv ├── drinks.csv ├── example.html ├── hitters.csv ├── imdb_1000.csv ├── imdb_ids.txt ├── sms.tsv ├── titanic.csv ├── u.data ├── u.item ├── u.user ├── ufo.csv ├── vehicles_test.csv ├── vehicles_train.csv ├── yelp.csv └── yelp.json ├── homework ├── 09_bias_variance.md ├── 09_glass_id.md ├── 10_yelp_reviews.md ├── 11_titanic.md ├── 12_roc_auc.md ├── 14_spam_filtering.md ├── 14_yelp_text.md └── 15_cross_validation.md ├── notebooks ├── 08_bias_variance.ipynb ├── 08_knn_sklearn.ipynb ├── 09_model_evaluation.ipynb ├── 10_linear_regression.ipynb ├── 11_logistic_regression.ipynb ├── 12_advanced_model_evaluation.ipynb ├── 12_roc_auc_rank_ordering.ipynb ├── 14_bayes_theorem_iris.ipynb ├── 14_naive_bayes_spam.ipynb ├── 15_cross_validation.ipynb ├── 15_natural_language_processing.ipynb ├── 17_decision_trees.ipynb ├── 18_ensembling.ipynb └── images │ ├── bias_variance.png │ ├── cross_validation_diagram.png │ ├── crowdflower_ensembling.jpg │ ├── driver_ensembling.png │ ├── estimating_coefficients.png │ ├── iris_01nn_map.png │ ├── iris_05nn_map.png │ ├── iris_15nn_map.png │ ├── iris_50nn_map.png │ ├── logistic_betas.png │ ├── obama_clinton_tree.jpg │ ├── r_squared.png │ ├── salary_color.png │ ├── salary_regions.png │ ├── salary_tree.png │ ├── salary_tree_annotated.png │ ├── salary_tree_deep.png │ ├── slope_intercept.png │ ├── supervised_learning.png │ ├── train_test_split.png │ ├── training_testing_error.png │ ├── tree_titanic.png │ ├── tree_vehicles.png │ └── tree_vs_linear.png ├── other ├── advice.md ├── python_packages.md └── setup_checklist.md ├── project ├── README.md ├── peer_review.md └── public_data.md └── slides ├── 01_course_overview.pdf ├── 01_course_overview.pptx ├── 01_intro_to_data_science.pdf ├── 01_intro_to_data_science.pptx ├── 01_types_of_data.pdf ├── 01_types_of_data.pptx ├── 02_git_github.pdf ├── 02_git_github.pptx ├── 06_machine_learning.pdf ├── 06_machine_learning.pptx ├── 11_confusion_matrix.pdf ├── 11_confusion_matrix.pptx ├── 12_drawing_roc.pdf ├── 12_drawing_roc.pptx ├── 14_bayes_theorem.pdf ├── 14_bayes_theorem.pptx ├── 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