OP 01 September, 2022 - 12:50 PM
Course: https://www.packtpub.com/product/data-cl...1803239040
Release Date: 2021
Duration: 3 hours, 33 minutes
Language: English
Owner: Mike West
Content:
Code:
./PacktPub - Data Cleansing Master Class in Python 5.91 GB
.pad 55.80 MB
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Section 1 314.27 MB
01.01-course_introduction.mkv 152.85 MB 160278554
01.02-course_structure.mkv 157.16 MB 164801946
01.03-is_this_course_right_for_you.mkv 4.25 MB 4460070
Section 2 1.73 GB
02.01-introducing_data_preparation.mkv 277.14 MB 290606714
02.02-the_machine_learning_process.mkv 90.77 MB 95182497
02.03-data_preparation_defined.mkv 251.93 MB 264173819
02.04-choosing_a_data_preparation_technique.mkv 264.02 MB 276846412
02.05-what_is_data_in_machine_learning.mkv 75.70 MB 79384833
02.06-raw_data.mkv 115.34 MB 120951425
02.07-machine_learning_is_mostly_data_preparation.mkv 29.11 MB 30526743
02.08-common_data_preparation_tasks-data_cleansing.mkv 160.18 MB 167969011
02.09-common_data_preparation_tasks-feature_selection.mkv 51.66 MB 54170861
02.10-common_data_preparation_tasks-data_transforms.mkv 10.45 MB 10967835
02.11-common_data_preparation_tasks-feature_engineering.mkv 134.62 MB 141162267
02.12-common_data_preparation_tasks-dimensionality_reduction.mkv 9.14 MB 9584140
02.13-data_leakage.mkv 11.27 MB 11821330
02.14-problem_with_naive_data_preparation.mkv 142.91 MB 149862051
02.15-case_study_data_leakage_train__test__split_naive_approach.mkv 46.89 MB 49169628
02.16-case_study_data_leakage_train__test__split_correct_approach.mkv 27.22 MB 28548152
02.17-case_study_data_leakage_k-fold_naive_approach.mkv 39.55 MB 41481637
02.18-case_study_data_leakage_k-fold_correct_approach.mkv 35.40 MB 37121061
Section 3 927.41 MB
03.01-data_cleansing_overview.mkv 159.66 MB 167419430
03.02-identify_columns_that_contain_a_single_value.mkv 18.12 MB 19005405
03.03-identify_columns_with_few_values.mkv 31.19 MB 32705727
03.04-remove_columns_with_low_variance.mkv 29.13 MB 30550435
03.05-identify_and_remove_rows_that_contain_duplicate_data.mkv 110.78 MB 116168228
03.06-defining_outliers.mkv 97.67 MB 102418418
03.07-remove_outliers-the_standard_deviation_approach.mkv 49.99 MB 52426575
03.08-remove_outliers-the_iqr_approach.mkv 40.67 MB 42653357
03.09-automatic_outlier_detection.mkv 50.21 MB 52657917
03.10-mark_missing_values.mkv 60.02 MB 62942856
03.11-remove_rows_with_missing_values.mkv 27.74 MB 29089147
03.12-statistical_imputation.mkv 5.97 MB 6266701
03.13-mean_value_imputation.mkv 41.86 MB 43893412
03.14-simple_imputer_with_model_evaluation.mkv 21.25 MB 22289208
03.15-compare_different_statistical_imputation_strategies.mkv 25.31 MB 26545189
03.16-k-nearest_neighbors_imputation.mkv 44.38 MB 46546262
03.17-knnimputer_and_model_evaluation.mkv 34.33 MB 36002433
03.18-iterative_imputation.mkv 37.61 MB 39438883
03.19-iterativeimputer_and_model_evaluation.mkv 18.40 MB 19302103
03.20-iterativeimputer_and_different_imputation_order.mkv 23.02 MB 24144987
Section 4 1.37 GB
04.01-feature_selection_introduction.mkv 203.11 MB 212980631
04.02-feature_selection_defined.mkv 11.87 MB 12456808
04.03-statistics_for_feature_selection.mkv 104.29 MB 109362154
04.04-loading_a_categorical_dataset.mkv 27.64 MB 28990616
04.05-encode_the_dataset_for_modelling.mkv 25.01 MB 26234382
04.06-chi-squared.mkv 17.48 MB 18334587
04.07-mutual_information.mkv 18.19 MB 19080596
04.08-modeling_with_selected_categorical_features.mkv 37.42 MB 39245739
04.09-feature_selection_with_anova_on_numerical_input.mkv 41.77 MB 43806597
04.10-feature_selection_with_mutual_information.mkv 18.20 MB 19088512
04.11-modeling_with_selected_numerical_features.mkv 25.98 MB 27246495
04.12-tuning_a_number_of_selected_features.mkv 37.96 MB 39813815
04.13-select_features_for_numerical_output.mkv 22.68 MB 23785625
04.14-linear_correlation_with_correlation_statistics.mkv 26.18 MB 27455204
04.15-linear_correlation_with_mutual_information.mkv 29.37 MB 30802438
04.16-baseline_and_model_built_using_correlation.mkv 35.73 MB 37470856
04.17-model_built_using_mutual_information_features.mkv 11.42 MB 11977012
04.18-tuning_number_of_selected_features.mkv 54.68 MB 57345569
04.19-recursive_feature_elimination.mkv 176.56 MB 185147007
04.20-rfe_for_classification.mkv 51.03 MB 53509811
04.21-rfe_for_regression.mkv 26.20 MB 27480482
04.22-rfe_hyperparameters.mkv 32.63 MB 34220431
04.23-feature_ranking_for_rfe.mkv 29.59 MB 31028758
04.24-feature_importance_scores_defined.mkv 187.16 MB 196258752
04.25-feature_importance_scores_linear_regression.mkv 35.14 MB 36856040
04.26-feature_importance_scores_logistic_regression_and_cart.mkv 36.53 MB 38307466
04.27-feature_importance_scores_random_forests.mkv 17.00 MB 17832945
04.28-permutation_feature_importance.mkv 28.40 MB 29785734
04.29-feature_selection_with_importance.mkv 42.35 MB 44410447
Section 5 858.73 MB
05.01-scale_numerical_data.mkv 11.06 MB 11600894
05.02-diabetes_dataset_for_scaling.mkv 23.03 MB 24155036
05.03-minmaxscaler_transform.mkv 24.25 MB 25431078
05.04-standardscaler_transform.mkv 28.50 MB 29885853
05.05-robust_scaling_data.mkv 42.48 MB 44550654
05.06-robust_scaler_applied_to_dataset.mkv 22.59 MB 23696418
05.07-explore_robust_scaler_range.mkv 14.90 MB 15630561
05.08-nominal_and_ordinal_variables.mkv 301.64 MB 316302042
05.09-ordinal_encoding.mkv 17.01 MB 17839280
05.10-one-hot_encoding_defined.mkv 3.70 MB 3880740
05.11-one-hot_encoding.mkv 17.26 MB 18106821
05.12-dummy_variable_encoding.mkv 17.46 MB 18311290
05.13-ordinal_encoder_transform_on_breast_cancer_dataset.mkv 45.66 MB 47879193
05.14-make_distributions_more_gaussian.mkv 8.88 MB 9311735
05.15-power_transform_on_contrived_dataset.mkv 21.33 MB 22376388
05.16-power_transform_on_sonar_dataset.mkv 28.99 MB 30399819
05.17-box-cox_on_sonar_dataset.mkv 31.77 MB 33320553
05.18-yeo-johnson_on_sonar_dataset.mkv 26.02 MB 27289785
05.19-polynomial_features.mkv 152.86 MB 160292017
05.20-effect_of_polynomial_degrees.mkv 19.24 MB 20184746
Section 6 471.16 MB
06.01-transforming_different_data_types.mkv 23.42 MB 24559318
06.02-the_columntransformer.mkv 28.22 MB 29594175
06.03-the_columntransformer_on_abalone_dataset.mkv 35.32 MB 37041371
06.04-manually_transform_target_variable.mkv 24.53 MB 25722029
06.05-automatically_transform_target_variable.mkv 54.43 MB 57078212
06.06-challenge_of_preparing_new_data_for_a_model.mkv 246.90 MB 258900775
06.07-save_model_and_data_scaler.mkv 40.38 MB 42341870
06.08-load_and_apply_saved_scalers.mkv 17.94 MB 18814309
Section 7 239.93 MB
07.01-curse_of_dimensionality.mkv 14.32 MB 15022150
07.02-techniques_for_dimensionality_reduction.mkv 97.49 MB 102228987
07.03-linear_discriminant_analysis.mkv 19.26 MB 20197281
07.04-linear_discriminant_analysis_demonstrated.mkv 49.10 MB 51491386
07.05-principal_component_analysis.mkv 59.74 MB 62650559
Exercises Files.zip 304.42 KB 311728Download:
