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

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文件数目：109个文件
文件大小：5.86 GB
收录时间：2022-01-12
访问次数：6
相关内容：PacktPub Data Cleansing Master Class Python

文件meta

Section 5/05.08-nominal_and_ordinal_variables.mkv
301.65 MB
Section 2/02.01-introducing_data_preparation.mkv
277.14 MB
Section 2/02.04-choosing_a_data_preparation_technique.mkv
264.02 MB
Section 2/02.03-data_preparation_defined.mkv
251.94 MB
Section 6/06.06-challenge_of_preparing_new_data_for_a_model.mkv
246.91 MB
Section 4/04.01-feature_selection_introduction.mkv
203.11 MB
Section 4/04.24-feature_importance_scores_defined.mkv
187.17 MB
Section 4/04.19-recursive_feature_elimination.mkv
176.57 MB
Section 2/02.08-common_data_preparation_tasks-data_cleansing.mkv
160.19 MB
Section 3/03.01-data_cleansing_overview.mkv
159.66 MB
Section 1/01.02-course_structure.mkv
157.17 MB
Section 5/05.19-polynomial_features.mkv
152.87 MB
Section 1/01.01-course_introduction.mkv
152.85 MB
Section 2/02.14-problem_with_naive_data_preparation.mkv
142.92 MB
Section 2/02.11-common_data_preparation_tasks-feature_engineering.mkv
134.62 MB
Section 2/02.06-raw_data.mkv
115.35 MB
Section 3/03.05-identify_and_remove_rows_that_contain_duplicate_data.mkv
110.79 MB
Section 4/04.03-statistics_for_feature_selection.mkv
104.3 MB
Section 3/03.06-defining_outliers.mkv
97.67 MB
Section 7/07.02-techniques_for_dimensionality_reduction.mkv
97.49 MB
Section 2/02.02-the_machine_learning_process.mkv
90.77 MB
Section 2/02.05-what_is_data_in_machine_learning.mkv
75.71 MB
Section 3/03.10-mark_missing_values.mkv
60.03 MB
Section 7/07.05-principal_component_analysis.mkv
59.75 MB
Section 4/04.18-tuning_number_of_selected_features.mkv
54.69 MB
Section 6/06.05-automatically_transform_target_variable.mkv
54.43 MB
Section 2/02.09-common_data_preparation_tasks-feature_selection.mkv
51.66 MB
Section 4/04.20-rfe_for_classification.mkv
51.03 MB
Section 3/03.09-automatic_outlier_detection.mkv
50.22 MB
Section 3/03.07-remove_outliers-the_standard_deviation_approach.mkv
50 MB
Section 7/07.04-linear_discriminant_analysis_demonstrated.mkv
49.11 MB
Section 2/02.15-case_study_data_leakage_train__test__split_naive_approach.mkv
46.89 MB
Section 5/05.13-ordinal_encoder_transform_on_breast_cancer_dataset.mkv
45.66 MB
Section 3/03.16-k-nearest_neighbors_imputation.mkv
44.39 MB
Section 5/05.05-robust_scaling_data.mkv
42.49 MB
Section 4/04.29-feature_selection_with_importance.mkv
42.35 MB
Section 3/03.13-mean_value_imputation.mkv
41.86 MB
Section 4/04.09-feature_selection_with_anova_on_numerical_input.mkv
41.78 MB
Section 3/03.08-remove_outliers-the_iqr_approach.mkv
40.68 MB
Section 6/06.07-save_model_and_data_scaler.mkv
40.38 MB
Section 2/02.17-case_study_data_leakage_k-fold_naive_approach.mkv
39.56 MB
Section 4/04.12-tuning_a_number_of_selected_features.mkv
37.97 MB
Section 3/03.18-iterative_imputation.mkv
37.61 MB
Section 4/04.08-modeling_with_selected_categorical_features.mkv
37.43 MB
Section 4/04.26-feature_importance_scores_logistic_regression_and_cart.mkv
36.53 MB
Section 4/04.16-baseline_and_model_built_using_correlation.mkv
35.73 MB
Section 2/02.18-case_study_data_leakage_k-fold_correct_approach.mkv
35.4 MB
Section 6/06.03-the_columntransformer_on_abalone_dataset.mkv
35.33 MB
Section 4/04.25-feature_importance_scores_linear_regression.mkv
35.15 MB
Section 3/03.17-knnimputer_and_model_evaluation.mkv
34.33 MB