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Language:
English
Total Size:
2.4 GB
Info Hash:
5E2425CFF95A526DE185B5568636AE783A71E7EE
Added By:
Added:
Jan. 13, 2025, 4:14 p.m.
Stats:
|
(Last updated: April 29, 2025, 1:56 p.m.)
| File | Size |
|---|---|
| Get Bonus Downloads Here.url | 183 bytes |
| 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 | 386 bytes |
| 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 |
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10.0 MB
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2023-06-23
| Uploaded by FreeCourseWeb | Size 10.0 MB | Health [ 8 /1 ] | Added 2023-06-23 |
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97.6 MB
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2023-07-01
| Uploaded by FreeCourseWeb | Size 97.6 MB | Health [ 0 /0 ] | Added 2023-07-01 |
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37.1 MB
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| Uploaded by FreeCourseWeb | Size 37.1 MB | Health [ 12 /9 ] | Added 2023-07-01 |
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| Uploaded by FreeCourseWeb | Size 11.1 MB | Health [ 12 /4 ] | Added 2023-07-01 |
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| Uploaded by FreeCourseWeb | Size 13.2 MB | Health [ 9 /1 ] | Added 2023-07-01 |
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SOURCE: Machine Learning with R the tidyverse and mlr Video Edition FreeCourseWeb
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