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00_lecture_notes 2.docx
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00_lecture_notes.pdf
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01_introduction_and_course_overview.pdf
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02_introduction_to_supervised_learning.pdf
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03_overfitting_in_linear_regression.pdf
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04_logistic_regression.pdf
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05_overfitting_logistic_regression.pdf
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06_lazy_learning.pdf
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07_naive_bayes.pdf
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08_multi_layer_perceptron.pdf
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09_support_vector_machines_(part_1).pdf
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10_support_vector_machines_(part_2).pdf
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11_multiclass_and_bias_variance_decomposition.pdf
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12_ensemble_methods.pdf
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13_probably_approximately_correct_learning.pdf
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14_decision.pdf
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15_introduction_to_unsupervised_learning.pdf
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16_feature_extraction.pdf
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17_introduction_to_clustering.pdf
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18_clustering_-_beyond_prototypes.pdf
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19_hierarchical_clustering.pdf
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20_fuzzy_clustering_and_manifold_learning.pdf
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