Machine Learning with R, the tidyverse, and mlr. Video Edition

Files:

• Get Bonus Downloads Here.url (0.2 KB)
~Get Your Files Here !
• Appendix._Central_tendency.mp4 (10.2 MB)
• Appendix._Distributions.mp4 (9.7 MB)
• Appendix._Logarithms.mp4 (9.2 MB)
• Appendix._Measures_of_dispersion.mp4 (21.2 MB)
• Appendix._Measures_of_the_relationships_between_variables.mp4 (10.7 MB)
• Appendix._Refresher_on_statistical_concepts.mp4 (17.4 MB)
• Appendix._Sigma_notation.mp4 (5.3 MB)
• Appendix.__Vectors.mp4 (5.8 MB)
• Bonus Resources.txt (0.4 KB)
• Chapter_1._Classes_of_machine_learning_algorithms.mp4 (40.5 MB)
• Chapter_1._Introduction_to_machine_learning.mp4 (34.1 MB)
• Chapter_1._Summary.mp4 (5.4 MB)
• Chapter_1._Thinking_about_the_ethical_impact_of_machine_learning.mp4 (20.4 MB)
• Chapter_1._What_will_you_learn_in_this_book.mp4 (2.6 MB)
• Chapter_1._Which_datasets_will_we_use.mp4 (2.0 MB)
• Chapter_1._Why_use_R_for_machine_learning.mp4 (8.0 MB)
• Chapter_10._Building_your_first_GAM.mp4 (19.1 MB)
• Chapter_10._More_flexibility_Splines_and_generalized_additive_models.mp4 (20.7 MB)
• Chapter_10._Strengths_and_weaknesses_of_GAMs.mp4 (3.8 MB)
• Chapter_10._Summary.mp4 (2.6 MB)
• Chapter_10.__Nonlinear_regression_with_generalized_additive_models.mp4 (18.5 MB)
• Chapter_11._Benchmarking_ridge,_LASSO,_elastic_net,_and_OLS_against_each_other.mp4 (7.3 MB)
• Chapter_11._Building_your_first_ridge,_LASSO,_and_elastic_net_models.mp4 (51.4 MB)
• Chapter_11._Preventing_overfitting_with_ridge_regression,_LASSO,_and_elastic_net.mp4 (7.0 MB)
• Chapter_11._Strengths_and_weaknesses_of_ridge,_LASSO,_and_elastic_net.mp4 (4.9 MB)
• Chapter_11._Summary.mp4 (4.8 MB)
• Chapter_11._What_is_elastic_net.mp4 (11.2 MB)
• Chapter_11._What_is_ridge_regression.mp4 (18.5 MB)
• Chapter_11._What_is_the_L1_norm,_and_how_does_LASSO_use_it.mp4 (8.3 MB)
• Chapter_11._What_is_the_L2_norm,_and_how_does_ridge_regression_use_it.mp4 (18.6 MB)
• Chapter_12._Benchmarking_the_kNN,_random_forest,_and_XGBoost_model-building_processes.mp4 (4.4 MB)
• Chapter_12._Building_your_first_XGBoost_regression_model.mp4 (12.2 MB)
• Chapter_12._Building_your_first_kNN_regression_model.mp4 (32.3 MB)
• Chapter_12._Building_your_first_random_forest_regression_model.mp4 (9.8 MB)
• Chapter_12._Regression_with_kNN,_random_forest,_and_XGBoost.mp4 (14.1 MB)
• Chapter_12._Strengths_and_weaknesses_of_kNN,_random_forest,_and_XGBoost.mp4 (2.5 MB)
• Chapter_12._Summary.mp4 (3.7 MB)
• Chapter_12._Using_tree-based_learners_to_predict_a_continuous_variable.mp4 (12.3 MB)
• Chapter_13._Building_your_first_PCA_model.mp4 (43.6 MB)
• Chapter_13._Maximizing_variance_with_principal_component_analysis.mp4 (31.4 MB)
• Chapter_13._Strengths_and_weaknesses_of_PCA.mp4 (2.7 MB)
• Chapter_13._Summary.mp4 (3.7 MB)
• Chapter_13._What_is_principal_component_analysis.mp4 (27.5 MB)
• Chapter_14._Building_your_first_UMAP_model.mp4 (17.4 MB)
• Chapter_14._Building_your_first_t-SNE_embedding.mp4 (25.2 MB)
• Chapter_14._Maximizing_similarity_with_t-SNE_and_UMAP.mp4 (35.2 MB)
• Chapter_14._Strengths_and_weaknesses_of_t-SNE_and_UMAP.mp4 (3.4 MB)
• Chapter_14._Summary.mp4 (3.2 MB)
• Chapter_14._What_is_UMAP.mp4 (16.5 MB)
• Chapter_15._Building_an_LLE_of_our_flea_data.mp4 (5.5 MB)
• Chapter_15._Building_your_first_LLE.mp4 (19.0 MB)
• Chapter_15._Building_your_first_SOM.mp4 (61.8 MB)
• Chapter_15._Self-organizing_maps_and_locally_linear_embedding.mp4 (12.6 MB)
• Chapter_15._Strengths_and_weaknesses_of_SOMs_and_LLE.mp4 (5.6 MB)
• Chapter_15._Summary.mp4 (3.9 MB)
• Chapter_15._What_are_self-organizing_maps.mp4 (31.1 MB)
• Chapter_15._What_is_locally_linear_embedding.mp4 (11.4 MB)
• Chapter_16._Building_your_first_k-means_model.mp4 (81.9 MB)
• Chapter_16._Clustering_by_finding_centers_with_k-means.mp4 (32.8 MB)
• Chapter_16._Strengths_and_weaknesses_of_k-means_clustering.mp4 (3.4 MB)
• Chapter_16._Summary.mp4 (2.8 MB)
• Chapter_17._Building_your_first_agglomerative_hierarchical_clustering_model.mp4 (56.6 MB)
• Chapter_17._Hierarchical_clustering.mp4 (33.9 MB)
• Chapter_17._How_stable_are_our_clusters.mp4 (11.5 MB)
• Chapter_17._Strengths_and_weaknesses_of_hierarchical_clustering.mp4 (6.0 MB)
• Chapter_17._Summary.mp4 (3.8 MB)
• Chapter_18._Building_your_first_DBSCAN_model.mp4 (69.8 MB)
• Chapter_18._Building_your_first_OPTICS_model.mp4 (9.8 MB)
• Chapter_18._Clustering_based_on_density_DBSCAN_and_OPTICS.mp4 (54.7 MB)
• Chapter_18._Strengths_and_weaknesses_of_density-based_clustering.mp4 (3.6 MB)
• Chapter_18._Summary.mp4 (5.0 MB)
• Chapter_19._Building_your_first_Gaussian_mixture_model_for_clustering.mp4 (20.3 MB)
• Chapter_19._Clustering_based_on_distributions_with_mixture_modeling.mp4 (44.5 MB)
• Chapter_19._Strengths_and_weaknesses_of_mixture_model_clustering.mp4 (4.5 MB)
• Chapter_19._Summary.mp4 (3.7 MB)
• Chapter_2._Loading_the_tidyverse.mp4 (536.9 KB)
• Chapter_2._Summary.mp4 (7.5 MB)
• Chapter_2._Tidying,_manipulating,_and_plotting_data_with_the_tidyverse.mp4 (14.4 MB)
• Chapter_2._What_the_dplyr_package_is_and_what_it_does.mp4 (19.0 MB)
• Chapter_2._What_the_ggplot2_package_is_and_what_it_does.mp4 (15.8 MB)
• Chapter_2._What_the_purrr_package_is_and_what_it_does.mp4 (25.3 MB)
• Chapter_2._What_the_tibble_package_is_and_what_it_does.mp4 (12.2 MB)
• Chapter_2._What_the_tidyr_package_is_and_what_it_does.mp4 (7.4 MB)
• Chapter_20._Final_notes_and_further_reading.mp4 (65.8 MB)
• Chapter_20._The_last_word.mp4 (1.4 MB)
• Chapter_20._Where_can_you_go_from_here.mp4 (22.1 MB)
• Chapter_3._Balancing_two_sources_of_model_error_The_bias-variance_trade-off.mp4 (16.0 MB)
• Chapter_3._Building_your_first_kNN_model.mp4 (26.0 MB)
• Chapter_3._Classifying_based_on_similarities_with_k-nearest_neighbors.mp4 (22.8 MB)
• Chapter_3._Cross-validating_our_kNN_model.mp4 (39.5 MB)
• Chapter_3._Strengths_and_weaknesses_of_kNN.mp4 (5.5 MB)
• Chapter_3._Summary.mp4 (9.3 MB)
• Chapter_3._Tuning_k_to_improve_the_model.mp4 (23.0 MB)
• Chapter_3._Using_cross-validation_to_tell_if_we_re_overfitting_or_underfitting.mp4 (6.6 MB)
• Chapter_3._What_algorithms_can_learn,_and_what_they_must_be_told_Parameters-_s_and_hyperparameters.mp4 (10.7 MB)
• Chapter_4._Building_your_first_logistic_regression_model.mp4 (40.8 MB)
• Chapter_4._Classifying_based_on_odds_with_logistic_regression.mp4 (55.3 MB)
• Chapter_4._Cross-validating_the_logistic_regression_model.mp4 (11.4 MB)
• Chapter_4._Interpreting_the_model_The_odds_ratio.mp4 (11.6 MB)
• Chapter_4._Strengths_and_weaknesses_of_logistic_regression.mp4 (5.0 MB)
• Chapter_4._Summary.mp4 (6.8 MB)
• Chapter_4._Using_our_model_to_make_predictions.mp4 (2.3 MB)
• Chapter_5._Building_your_first_linear_and_quadratic_discriminant_models.mp4 (21.0 MB)
• Chapter_5._Classifying_by_maximizing_separation_with_discriminant_analysis.mp4 (56.8 MB)
• Chapter_5._Strengths_and_weaknesses_of_LDA_and_QDA.mp4 (4.9 MB)
• Chapter_5._Summary.mp4 (5.5 MB)
• Chapter_6._Building_your_first_SVM_model.mp4 (33.0 MB)
• Chapter_6._Building_your_first_naive_Bayes_model.mp4 (17.1 MB)
• Chapter_6._Classifying_with_naive_Bayes_and_support_vector_machines.mp4 (31.9 MB)
• Chapter_6._Cross-validating_our_SVM_model.mp4 (7.0 MB)
• Chapter_6._Strengths_and_weaknesses_of_naive_Bayes.mp4 (2.8 MB)
• Chapter_6._Strengths_and_weaknesses_of_the_SVM_algorithm.mp4 (3.5 MB)
• Chapter_6._Summary.mp4 (5.9 MB)
• Chapter_6._What_is_the_support_vector_machine_(SVM)_algorithm.mp4 (59.4 MB)
• Chapter_7._Building_your_first_decision_tree_model.mp4 (2.8 MB)
• Chapter_7._Classifying_with_decision_trees.mp4 (50.2 MB)
• Chapter_7._Cross-validating_our_decision_tree_model.mp4 (7.3 MB)
• Chapter_7._Loading_and_exploring_the_zoo_dataset.mp4 (3.1 MB)
• Chapter_7._Strengths_and_weaknesses_of_tree-based_algorithms.mp4 (1.8 MB)
• Chapter_7._Summary.mp4 (2.2 MB)
• Chapter_7._Training_the_decision_tree_model.mp4 (30.0 MB)
• Chapter_8._Benchmarking_algorithms_against_each_other.mp4 (7.0 MB)
• Chapter_8._Building_your_first_XGBoost_model.mp4 (21.6 MB)
• Chapter_8._Building_your_first_random_forest_model.mp4 (12.8 MB)
• Chapter_8._Improving_decision_trees_with_random_forests_and_boosting.mp4 (59.7 MB)
• Chapter_8._Strengths_and_weaknesses_of_tree-based_algorithms.mp4 (3.0 MB)
• Chapter_8._Summary.mp4 (3.4 MB)
• Chapter_9._Building_your_first_linear_regression_model.mp4 (120.1 MB)
• Chapter_9._Linear_regression.mp4 (49.1 MB)
• Chapter_9._Strengths_and_weaknesses_of_linear_regression.mp4 (3.1 MB)
• Chapter_9._Summary.mp4 (3.9 MB)
• Part_1._Introduction.mp4 (5.4 MB)
• Part_2._Classification.mp4 (5.3 MB)
• Part_3._Regression.mp4 (4.3 MB)
• Part_4._Dimension_reduction.mp4 (3.6 MB)
• Part_5._Clustering.mp4 (3.0 MB)