mlpy：使用Python进行机器学习的亲身实践研讨会
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2021-02-04
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mlpy：使用Python进行机器学习的亲身实践研讨会 （226个子文件） 
weather-stations20140101-20141231.csv 127KB FuelConsumption.csv 71KB teleCust1000t.csv 36KB ChurnData.csv 35KB Cust_Segmentation.csv 33KB automobile-checkpoint.csv 25KB cell_samples.csv 20KB cars_clus.csv 17KB drug200.csv 6KB china_gdp.csv 1KB .gitignore 1KB 04_Clustering.ipynb 2.95MB 03_Classification.ipynb 541KB 02_Regression.ipynb 282KB 05_Recommender.ipynb 120KB 01_Intro.ipynb 14KB deliver-checkpoint.ipynb 9KB deliver.ipynb 9KB 00_Outline.ipynb 3KB LICENSE 1KB README.md 10KB CODE_OF_CONDUCT.md 3KB CONTRIBUTING.md 1KB
dbscan_stations.png 1.64MB dbscan_groups_of_stations.png 1.63MB what_are_recommender_systems.png 1.59MB benign_malignant.png 1.43MB hierarchical_clustering.png 1.22MB k_fold_cross_validation.png 1.01MB applications.png 980KB user_based_vs_item_based.png 944KB how_content_based_recsys_works.png 930KB model_prediction.png 902KB types_recommender_systems.png 897KB other_genre_problem.png 895KB distance_between_clusters.png 891KB classification_with_svm.png 852KB cross_join_segmented_dataset.png 824KB predicted_ratings_for_user.png 813KB hierarchical_clustering_vs_k_means.png 789KB what_is_svm_plane.png 781KB k_means_vs_density_with_density.png 762KB calculate_similarity_multi.png 759KB what_is_dbscan.png 759KB user_based_collaborative_filtering.png 757KB train_test_split_vs_train_test_same_dataset.png 753KB clustering_for_segmentation.png 747KB what_is_k_means_clustering.png 745KB clustering_vs_classification.png 728KB implement_recommender_systems.png 719KB logistic_regression_applications.png 703KB k_means_vs_density_with_k_means.png 700KB user_profile.png 700KB calculate_similarity_2d.png 698KB compute_new_centroids.png 694KB supervised_vs_unsupervised.png 694KB assign_centroid.png 689KB when_use_logistic_regression.png 683KB training_out_of_sample_accuracy.png 678KB unsupervised.png 677KB knn_algorithm.png 669KB k_means_algorithms.png 662KB clustering_applications_financial.png 661KB agglomerative_example_completed.png 660KB learn_similarity_weights.png 659KB multiple_examples.png 654KB user_ratings_movies_matrix.png 653KB what_is_svm_curve.png 652KB spherical_vs_arbitary.png 646KB polynomial_regression.png 645KB clustering_algorithms.png 641KB k_means_algorithm.png 639KB what_is_decision_trees.png 635KB applications_recommender_systems.png 634KB what_is_clustering.png 630KB pros_cons_hierarchical_clustering.png 630KB approaches_collaborative_filtering.png 625KB scikit-learn.png 621KB agglomerative_example_first.png 619KB k_means_vs_density_points_outliers.png 618KB calculate_distance.png 614KB recommendation_matrix.png 613KB calculate_information_gain.png 610KB multiple.png 610KB non_linear_regression.png 607KB multi_dimentional_similarity.png 604KB ml_libraries.png 604KB dendrogram.png 602KB calculate_similarity_1d.png 602KB types.png 599KB agglomerative_algorithm.png 598KB create_weighted_ratings_matrix.png 598KB decision_tree_algorithm.png 594KB logistic_regression_training_process.png 593KB what_is_knn.png 592KB log_loss.png 588KB evaluation_apporaches.png 587KB candidate_movies.png 585KB classification.png 585KB agglomerative_example_before.png 584KB共 226 条
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