Name		Name	Last commit message	Last commit date
Latest commit History 32 Commits
.gitignore		.gitignore
README.md		README.md
lecture_01_introduction.pdf		lecture_01_introduction.pdf
lecture_02_feature_similarity.pdf		lecture_02_feature_similarity.pdf
lecture_03_convexity_optimization.pdf		lecture_03_convexity_optimization.pdf
lecture_04_ordinary_least_squares.pdf		lecture_04_ordinary_least_squares.pdf
lecture_04_pre_numpy.ipynb		lecture_04_pre_numpy.ipynb
lecture_05_ols2.pdf		lecture_05_ols2.pdf
lecture_06_regularization_robustreg.pdf		lecture_06_regularization_robustreg.pdf
lecture_07_stumps_n_trees.pdf		lecture_07_stumps_n_trees.pdf
lecture_08_trees_2_neighbors.pdf		lecture_08_trees_2_neighbors.pdf
lecture_09_logistic_regression.pdf		lecture_09_logistic_regression.pdf
lecture_10_error_metrics.pdf		lecture_10_error_metrics.pdf
lecture_11_cross_validation.pdf		lecture_11_cross_validation.pdf
lecture_12_model_selection.pdf		lecture_12_model_selection.pdf
lecture_14_exam_review.pdf		lecture_14_exam_review.pdf
lecture_16_solvers_and_finishing_model_selection.pdf		lecture_16_solvers_and_finishing_model_selection.pdf
lecture_17_svm.pdf		lecture_17_svm.pdf
lecture_18_bagging.pdf		lecture_18_bagging.pdf
lecture_19_boosting.pdf		lecture_19_boosting.pdf
lecture_20_perceptrons.pdf		lecture_20_perceptrons.pdf
lecture_21_backprop.pdf		lecture_21_backprop.pdf
lecture_23_exam2_review.pdf		lecture_23_exam2_review.pdf
lecture_25_ai_good_and_bad.pdf		lecture_25_ai_good_and_bad.pdf

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