[FreeCoursesOnline.Me] PacktPub - Data Cleansing Master Class in Python torrent, magnet, bt

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[FreeCoursesOnline.Me] PacktPub - Data Cleansing Master Class in Python

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2022-01-09

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FreeCoursesOnline Me PacktPub Data Cleansing Master Class in Python

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Size

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377B

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Exercises Files.zip

304.42KB

Section 1/01.01-course_introduction.mkv

152.85MB

Section 1/01.02-course_structure.mkv

157.17MB

Section 1/01.03-is_this_course_right_for_you.mkv

4.25MB

Section 2/02.01-introducing_data_preparation.mkv

277.14MB

Section 2/02.02-the_machine_learning_process.mkv

90.77MB

Section 2/02.03-data_preparation_defined.mkv

251.94MB

Section 2/02.04-choosing_a_data_preparation_technique.mkv

264.02MB

Section 2/02.05-what_is_data_in_machine_learning.mkv

75.71MB

Section 2/02.06-raw_data.mkv

115.35MB

Section 2/02.07-machine_learning_is_mostly_data_preparation.mkv

29.11MB

Section 2/02.08-common_data_preparation_tasks-data_cleansing.mkv

160.19MB

Section 2/02.09-common_data_preparation_tasks-feature_selection.mkv

51.66MB

Section 2/02.10-common_data_preparation_tasks-data_transforms.mkv

10.46MB

Section 2/02.11-common_data_preparation_tasks-feature_engineering.mkv

134.62MB

Section 2/02.12-common_data_preparation_tasks-dimensionality_reduction.mkv

9.14MB

Section 2/02.13-data_leakage.mkv

11.27MB

Section 2/02.14-problem_with_naive_data_preparation.mkv

142.92MB

Section 2/02.15-case_study_data_leakage_train__test__split_naive_approach.mkv

46.89MB

Section 2/02.16-case_study_data_leakage_train__test__split_correct_approach.mkv

27.23MB

Section 2/02.17-case_study_data_leakage_k-fold_naive_approach.mkv

39.56MB

Section 2/02.18-case_study_data_leakage_k-fold_correct_approach.mkv

35.4MB

Section 3/03.01-data_cleansing_overview.mkv

159.66MB

Section 3/03.02-identify_columns_that_contain_a_single_value.mkv

18.12MB

Section 3/03.03-identify_columns_with_few_values.mkv

31.19MB

Section 3/03.04-remove_columns_with_low_variance.mkv

29.14MB

Section 3/03.05-identify_and_remove_rows_that_contain_duplicate_data.mkv

110.79MB

Section 3/03.06-defining_outliers.mkv

97.67MB

Section 3/03.07-remove_outliers-the_standard_deviation_approach.mkv

50MB

Section 3/03.08-remove_outliers-the_iqr_approach.mkv

40.68MB

Section 3/03.09-automatic_outlier_detection.mkv

50.22MB

Section 3/03.10-mark_missing_values.mkv

60.03MB

Section 3/03.11-remove_rows_with_missing_values.mkv

27.74MB

Section 3/03.12-statistical_imputation.mkv

5.98MB

Section 3/03.13-mean_value_imputation.mkv

41.86MB

Section 3/03.14-simple_imputer_with_model_evaluation.mkv

21.26MB

Section 3/03.15-compare_different_statistical_imputation_strategies.mkv

25.32MB

Section 3/03.16-k-nearest_neighbors_imputation.mkv

44.39MB

Section 3/03.17-knnimputer_and_model_evaluation.mkv

34.33MB

Section 3/03.18-iterative_imputation.mkv

37.61MB

Section 3/03.19-iterativeimputer_and_model_evaluation.mkv

18.41MB

Section 3/03.20-iterativeimputer_and_different_imputation_order.mkv

23.03MB

Section 4/04.01-feature_selection_introduction.mkv

203.11MB

Section 4/04.02-feature_selection_defined.mkv

11.88MB

Section 4/04.03-statistics_for_feature_selection.mkv

104.3MB

Section 4/04.04-loading_a_categorical_dataset.mkv

27.65MB

Section 4/04.05-encode_the_dataset_for_modelling.mkv

25.02MB

Section 4/04.06-chi-squared.mkv

17.49MB

Section 4/04.07-mutual_information.mkv

18.2MB

Section 4/04.08-modeling_with_selected_categorical_features.mkv

37.43MB

Section 4/04.09-feature_selection_with_anova_on_numerical_input.mkv

41.78MB

Section 4/04.10-feature_selection_with_mutual_information.mkv

18.2MB

Section 4/04.11-modeling_with_selected_numerical_features.mkv

25.98MB

Section 4/04.12-tuning_a_number_of_selected_features.mkv

37.97MB

Section 4/04.13-select_features_for_numerical_output.mkv

22.68MB

Section 4/04.14-linear_correlation_with_correlation_statistics.mkv

26.18MB

Section 4/04.15-linear_correlation_with_mutual_information.mkv

29.38MB

Section 4/04.16-baseline_and_model_built_using_correlation.mkv

35.73MB

Section 4/04.17-model_built_using_mutual_information_features.mkv

11.42MB

Section 4/04.18-tuning_number_of_selected_features.mkv

54.69MB

Section 4/04.19-recursive_feature_elimination.mkv

176.57MB

Section 4/04.20-rfe_for_classification.mkv

51.03MB

Section 4/04.21-rfe_for_regression.mkv

26.21MB

Section 4/04.22-rfe_hyperparameters.mkv

32.64MB

Section 4/04.23-feature_ranking_for_rfe.mkv

29.59MB

Section 4/04.24-feature_importance_scores_defined.mkv

187.17MB

Section 4/04.25-feature_importance_scores_linear_regression.mkv

35.15MB

Section 4/04.26-feature_importance_scores_logistic_regression_and_cart.mkv

36.53MB

Section 4/04.27-feature_importance_scores_random_forests.mkv

17.01MB

Section 4/04.28-permutation_feature_importance.mkv

28.41MB

Section 4/04.29-feature_selection_with_importance.mkv

42.35MB

Section 5/05.01-scale_numerical_data.mkv

11.06MB

Section 5/05.02-diabetes_dataset_for_scaling.mkv

23.04MB

Section 5/05.03-minmaxscaler_transform.mkv

24.25MB

Section 5/05.04-standardscaler_transform.mkv

28.5MB

Section 5/05.05-robust_scaling_data.mkv

42.49MB

Section 5/05.06-robust_scaler_applied_to_dataset.mkv

22.6MB

Section 5/05.07-explore_robust_scaler_range.mkv

14.91MB

Section 5/05.08-nominal_and_ordinal_variables.mkv

301.65MB

Section 5/05.09-ordinal_encoding.mkv

17.01MB

Section 5/05.10-one-hot_encoding_defined.mkv

3.7MB

Section 5/05.11-one-hot_encoding.mkv

17.27MB

Section 5/05.12-dummy_variable_encoding.mkv

17.46MB

Section 5/05.13-ordinal_encoder_transform_on_breast_cancer_dataset.mkv

45.66MB

Section 5/05.14-make_distributions_more_gaussian.mkv

8.88MB

Section 5/05.15-power_transform_on_contrived_dataset.mkv

21.34MB

Section 5/05.16-power_transform_on_sonar_dataset.mkv

28.99MB

Section 5/05.17-box-cox_on_sonar_dataset.mkv

31.78MB

Section 5/05.18-yeo-johnson_on_sonar_dataset.mkv

26.03MB

Section 5/05.19-polynomial_features.mkv

152.87MB

Section 5/05.20-effect_of_polynomial_degrees.mkv

19.25MB

Section 6/06.01-transforming_different_data_types.mkv

23.42MB

Section 6/06.02-the_columntransformer.mkv

28.22MB

Section 6/06.03-the_columntransformer_on_abalone_dataset.mkv

35.33MB

Section 6/06.04-manually_transform_target_variable.mkv

24.53MB

Section 6/06.05-automatically_transform_target_variable.mkv

54.43MB

Section 6/06.06-challenge_of_preparing_new_data_for_a_model.mkv

246.91MB

Section 6/06.07-save_model_and_data_scaler.mkv

40.38MB

Section 6/06.08-load_and_apply_saved_scalers.mkv

17.94MB

Section 7/07.01-curse_of_dimensionality.mkv

14.33MB

Section 7/07.02-techniques_for_dimensionality_reduction.mkv

97.49MB

Section 7/07.03-linear_discriminant_analysis.mkv

19.26MB

Section 7/07.04-linear_discriminant_analysis_demonstrated.mkv

49.11MB

Section 7/07.05-principal_component_analysis.mkv

59.75MB

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