auxiliary_probability_distributions.one
auxiliary_probability_distributions.pdf
class_01a_jupyter_test.ipynb
class_01b_first_encounter.ipynb
class_02_numpy_pandas.ipynb
class_03_evaluation_and_testing.ipynb
class_04_content_based_recommenders.ipynb
class_05_amazon_recommender.ipynb
class_06_neighborhood_methods.ipynb
class_07_dimensionality_reduction_optimization.ipynb
class_08_netflix_recommender.ipynb
class_09_least_squares_and_mle.ipynb
class_10_neural_networks.ipynb
class_12_generalized_matrix_factorization.ipynb
class_13_youtube_recommender.ipynb
lecture_01_recommender_systems_introduction.pdf
lecture_01_recommender_systems_introduction.pptx
lecture_02_numpy_pandas.ipynb
lecture_03_evaluation_and_testing.ipynb
lecture_03_recommender_systems_evaluation_and_testing.pdf
lecture_03_recommender_systems_evaluation_and_testing.pptx
lecture_04_content_based_recommenders.ipynb
lecture_04_content_based_recommenders.one
lecture_04_content_based_recommenders.pdf
lecture_05_amazon_recommender.ipynb
lecture_05_amazon_recommender.one
lecture_05_amazon_recommender.pdf
lecture_06_neighborhood_methods.ipynb
lecture_06_neighborhood_methods.one
lecture_06_neighborhood_methods.pdf
lecture_07_dimensionality_reduction_matrix_factorization.one
lecture_07_dimensionality_reduction_matrix_factorization.pdf
lecture_07_optimization.one
lecture_07_optimization.pdf
lecture_08_gomez-uribe_hunt_netflix_recommender_algorithms_business_value_2015.pdf
lecture_08_koren_bell_volinsky_matrix_factorization_for_recommender_systems_2009.pdf
lecture_08_netflix_recommender.ipynb
lecture_09_least_squares_and_mle.one
lecture_09_least_squares_and_mle.pdf
lecture_10_neural_networks.one
lecture_10_neural_networks.pdf
lecture_12_generalized_matrix_factorization.ipynb
lecture_12_he_et_al_neural_collaborative_filtering_2017.pdf
lecture_13-14_youtube_recommender.one
lecture_13-14_youtube_recommender.pdf
project_1_data_preparation.ipynb
project_1_recommender_and_evaluation.ipynb
project_2_recommender_and_evaluation.ipynb
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