PacktPub - Data Cleansing Master Class in Python

磁力链接/BT种子名称

PacktPub - Data Cleansing Master Class in Python

磁力链接/BT种子简介

种子哈希：542c9944d3404a8babbf129a40e4e0982d996f97
文件大小： 5.91G
已经下载：2386次
下载速度：极快
收录时间：2022-01-19
最近下载：2025-02-17

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文件列表

  • Section 5/05.08-nominal_and_ordinal_variables.mkv 316.3 MB
  • Section 2/02.01-introducing_data_preparation.mkv 290.6 MB
  • Section 2/02.04-choosing_a_data_preparation_technique.mkv 276.8 MB
  • Section 2/02.03-data_preparation_defined.mkv 264.2 MB
  • Section 6/06.06-challenge_of_preparing_new_data_for_a_model.mkv 258.9 MB
  • Section 4/04.01-feature_selection_introduction.mkv 213.0 MB
  • Section 4/04.24-feature_importance_scores_defined.mkv 196.3 MB
  • Section 4/04.19-recursive_feature_elimination.mkv 185.1 MB
  • Section 2/02.08-common_data_preparation_tasks-data_cleansing.mkv 168.0 MB
  • Section 3/03.01-data_cleansing_overview.mkv 167.4 MB
  • Section 1/01.02-course_structure.mkv 164.8 MB
  • Section 5/05.19-polynomial_features.mkv 160.3 MB
  • Section 1/01.01-course_introduction.mkv 160.3 MB
  • Section 2/02.14-problem_with_naive_data_preparation.mkv 149.9 MB
  • Section 2/02.11-common_data_preparation_tasks-feature_engineering.mkv 141.2 MB
  • Section 2/02.06-raw_data.mkv 121.0 MB
  • Section 3/03.05-identify_and_remove_rows_that_contain_duplicate_data.mkv 116.2 MB
  • Section 4/04.03-statistics_for_feature_selection.mkv 109.4 MB
  • Section 3/03.06-defining_outliers.mkv 102.4 MB
  • Section 7/07.02-techniques_for_dimensionality_reduction.mkv 102.2 MB
  • Section 2/02.02-the_machine_learning_process.mkv 95.2 MB
  • Section 2/02.05-what_is_data_in_machine_learning.mkv 79.4 MB
  • Section 3/03.10-mark_missing_values.mkv 62.9 MB
  • Section 7/07.05-principal_component_analysis.mkv 62.7 MB
  • Section 4/04.18-tuning_number_of_selected_features.mkv 57.3 MB
  • Section 6/06.05-automatically_transform_target_variable.mkv 57.1 MB
  • Section 2/02.09-common_data_preparation_tasks-feature_selection.mkv 54.2 MB
  • Section 4/04.20-rfe_for_classification.mkv 53.5 MB
  • Section 3/03.09-automatic_outlier_detection.mkv 52.7 MB
  • Section 3/03.07-remove_outliers-the_standard_deviation_approach.mkv 52.4 MB
  • Section 7/07.04-linear_discriminant_analysis_demonstrated.mkv 51.5 MB
  • Section 2/02.15-case_study_data_leakage_train__test__split_naive_approach.mkv 49.2 MB
  • Section 5/05.13-ordinal_encoder_transform_on_breast_cancer_dataset.mkv 47.9 MB
  • Section 3/03.16-k-nearest_neighbors_imputation.mkv 46.5 MB
  • Section 5/05.05-robust_scaling_data.mkv 44.6 MB
  • Section 4/04.29-feature_selection_with_importance.mkv 44.4 MB
  • Section 3/03.13-mean_value_imputation.mkv 43.9 MB
  • Section 4/04.09-feature_selection_with_anova_on_numerical_input.mkv 43.8 MB
  • Section 3/03.08-remove_outliers-the_iqr_approach.mkv 42.7 MB
  • Section 6/06.07-save_model_and_data_scaler.mkv 42.3 MB
  • Section 2/02.17-case_study_data_leakage_k-fold_naive_approach.mkv 41.5 MB
  • Section 4/04.12-tuning_a_number_of_selected_features.mkv 39.8 MB
  • Section 3/03.18-iterative_imputation.mkv 39.4 MB
  • Section 4/04.08-modeling_with_selected_categorical_features.mkv 39.2 MB
  • Section 4/04.26-feature_importance_scores_logistic_regression_and_cart.mkv 38.3 MB
  • Section 4/04.16-baseline_and_model_built_using_correlation.mkv 37.5 MB
  • Section 2/02.18-case_study_data_leakage_k-fold_correct_approach.mkv 37.1 MB
  • Section 6/06.03-the_columntransformer_on_abalone_dataset.mkv 37.0 MB
  • Section 4/04.25-feature_importance_scores_linear_regression.mkv 36.9 MB
  • Section 3/03.17-knnimputer_and_model_evaluation.mkv 36.0 MB
  • Section 4/04.22-rfe_hyperparameters.mkv 34.2 MB
  • Section 5/05.17-box-cox_on_sonar_dataset.mkv 33.3 MB
  • Section 3/03.03-identify_columns_with_few_values.mkv 32.7 MB
  • Section 4/04.23-feature_ranking_for_rfe.mkv 31.0 MB
  • Section 4/04.15-linear_correlation_with_mutual_information.mkv 30.8 MB
  • Section 3/03.04-remove_columns_with_low_variance.mkv 30.6 MB
  • Section 2/02.07-machine_learning_is_mostly_data_preparation.mkv 30.5 MB
  • Section 5/05.16-power_transform_on_sonar_dataset.mkv 30.4 MB
  • Section 5/05.04-standardscaler_transform.mkv 29.9 MB
  • Section 4/04.28-permutation_feature_importance.mkv 29.8 MB
  • Section 6/06.02-the_columntransformer.mkv 29.6 MB
  • Section 3/03.11-remove_rows_with_missing_values.mkv 29.1 MB
  • Section 4/04.04-loading_a_categorical_dataset.mkv 29.0 MB
  • Section 2/02.16-case_study_data_leakage_train__test__split_correct_approach.mkv 28.5 MB
  • Section 4/04.21-rfe_for_regression.mkv 27.5 MB
  • Section 4/04.14-linear_correlation_with_correlation_statistics.mkv 27.5 MB
  • Section 5/05.18-yeo-johnson_on_sonar_dataset.mkv 27.3 MB
  • Section 4/04.11-modeling_with_selected_numerical_features.mkv 27.2 MB
  • Section 3/03.15-compare_different_statistical_imputation_strategies.mkv 26.5 MB
  • Section 4/04.05-encode_the_dataset_for_modelling.mkv 26.2 MB
  • Section 6/06.04-manually_transform_target_variable.mkv 25.7 MB
  • Section 5/05.03-minmaxscaler_transform.mkv 25.4 MB
  • Section 6/06.01-transforming_different_data_types.mkv 24.6 MB
  • Section 5/05.02-diabetes_dataset_for_scaling.mkv 24.2 MB
  • Section 3/03.20-iterativeimputer_and_different_imputation_order.mkv 24.1 MB
  • Section 4/04.13-select_features_for_numerical_output.mkv 23.8 MB
  • Section 5/05.06-robust_scaler_applied_to_dataset.mkv 23.7 MB
  • Section 5/05.15-power_transform_on_contrived_dataset.mkv 22.4 MB
  • Section 3/03.14-simple_imputer_with_model_evaluation.mkv 22.3 MB
  • Section 7/07.03-linear_discriminant_analysis.mkv 20.2 MB
  • Section 5/05.20-effect_of_polynomial_degrees.mkv 20.2 MB
  • Section 3/03.19-iterativeimputer_and_model_evaluation.mkv 19.3 MB
  • Section 4/04.10-feature_selection_with_mutual_information.mkv 19.1 MB
  • Section 4/04.07-mutual_information.mkv 19.1 MB
  • Section 3/03.02-identify_columns_that_contain_a_single_value.mkv 19.0 MB
  • Section 6/06.08-load_and_apply_saved_scalers.mkv 18.8 MB
  • Section 4/04.06-chi-squared.mkv 18.3 MB
  • Section 5/05.12-dummy_variable_encoding.mkv 18.3 MB
  • Section 5/05.11-one-hot_encoding.mkv 18.1 MB
  • Section 5/05.09-ordinal_encoding.mkv 17.8 MB
  • Section 4/04.27-feature_importance_scores_random_forests.mkv 17.8 MB
  • Section 5/05.07-explore_robust_scaler_range.mkv 15.6 MB
  • Section 7/07.01-curse_of_dimensionality.mkv 15.0 MB
  • Section 4/04.02-feature_selection_defined.mkv 12.5 MB
  • Section 4/04.17-model_built_using_mutual_information_features.mkv 12.0 MB
  • Section 2/02.13-data_leakage.mkv 11.8 MB
  • Section 5/05.01-scale_numerical_data.mkv 11.6 MB
  • Section 2/02.10-common_data_preparation_tasks-data_transforms.mkv 11.0 MB
  • Section 2/02.12-common_data_preparation_tasks-dimensionality_reduction.mkv 9.6 MB
  • Section 5/05.14-make_distributions_more_gaussian.mkv 9.3 MB
  • Section 3/03.12-statistical_imputation.mkv 6.3 MB
  • Section 1/01.03-is_this_course_right_for_you.mkv 4.5 MB
  • Section 5/05.10-one-hot_encoding_defined.mkv 3.9 MB
  • .pad/1041423 1.0 MB
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  • Exercises Files.zip 311.7 kB
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