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[FreeCoursesOnline Me] PacktPub - Data Cleansing Master Class in Python
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Exercises Files.zip
Section 1
01.01-course_introduction.mkv
01.02-course_structure.mkv
01.03-is_this_course_right_for_you.mkv
Section 2
02.01-introducing_data_preparation.mkv
02.02-the_machine_learning_process.mkv
02.03-data_preparation_defined.mkv
02.04-choosing_a_data_preparation_technique.mkv
02.05-what_is_data_in_machine_learning.mkv
02.06-raw_data.mkv
02.07-machine_learning_is_mostly_data_preparation.mkv
02.08-common_data_preparation_tasks-data_cleansing.mkv
02.09-common_data_preparation_tasks-feature_selection.mkv
02.10-common_data_preparation_tasks-data_transforms.mkv
02.11-common_data_preparation_tasks-feature_engineering.mkv
02.12-common_data_preparation_tasks-dimensionality_reduction.mkv
02.13-data_leakage.mkv
02.14-problem_with_naive_data_preparation.mkv
02.15-case_study_data_leakage_train__test__split_naive_approach.mkv
02.16-case_study_data_leakage_train__test__split_correct_approach.mkv
02.17-case_study_data_leakage_k-fold_naive_approach.mkv
02.18-case_study_data_leakage_k-fold_correct_approach.mkv
Section 3
03.01-data_cleansing_overview.mkv
03.02-identify_columns_that_contain_a_single_value.mkv
03.03-identify_columns_with_few_values.mkv
03.04-remove_columns_with_low_variance.mkv
03.05-identify_and_remove_rows_that_contain_duplicate_data.mkv
03.06-defining_outliers.mkv
03.07-remove_outliers-the_standard_deviation_approach.mkv
03.08-remove_outliers-the_iqr_approach.mkv
03.09-automatic_outlier_detection.mkv
03.10-mark_missing_values.mkv
03.11-remove_rows_with_missing_values.mkv
03.12-statistical_imputation.mkv
03.13-mean_value_imputation.mkv
03.14-simple_imputer_with_model_evaluation.mkv
03.15-compare_different_statistical_imputation_strategies.mkv
03.16-k-nearest_neighbors_imputation.mkv
03.17-knnimputer_and_model_evaluation.mkv
03.18-iterative_imputation.mkv
03.19-iterativeimputer_and_model_evaluation.mkv
03.20-iterativeimputer_and_different_imputation_order.mkv
Section 4
04.01-feature_selection_introduction.mkv
04.02-feature_selection_defined.mkv
04.03-statistics_for_feature_selection.mkv
04.04-loading_a_categorical_dataset.mkv
04.05-encode_the_dataset_for_modelling.mkv
04.06-chi-squared.mkv
04.07-mutual_information.mkv
04.08-modeling_with_selected_categorical_features.mkv
04.09-feature_selection_with_anova_on_numerical_input.mkv
04.10-feature_selection_with_mutual_information.mkv
04.11-modeling_with_selected_numerical_features.mkv
04.12-tuning_a_number_of_selected_features.mkv
04.13-select_features_for_numerical_output.mkv
04.14-linear_correlation_with_correlation_statistics.mkv
04.15-linear_correlation_with_mutual_information.mkv
04.16-baseline_and_model_built_using_correlation.mkv
04.17-model_built_using_mutual_information_features.mkv
04.18-tuning_number_of_selected_features.mkv
04.19-recursive_feature_elimination.mkv
04.20-rfe_for_classification.mkv
04.21-rfe_for_regression.mkv
04.22-rfe_hyperparameters.mkv
04.23-feature_ranking_for_rfe.mkv
04.24-feature_importance_scores_defined.mkv
04.25-feature_importance_scores_linear_regression.mkv
04.26-feature_importance_scores_logistic_regression_and_cart.mkv
04.27-feature_importance_scores_random_forests.mkv
04.28-permutation_feature_importance.mkv
04.29-feature_selection_with_importance.mkv
Section 5
05.01-scale_numerical_data.mkv
05.02-diabetes_dataset_for_scaling.mkv
05.03-minmaxscaler_transform.mkv
05.04-standardscaler_transform.mkv
05.05-robust_scaling_data.mkv
05.06-robust_scaler_applied_to_dataset.mkv
05.07-explore_robust_scaler_range.mkv
05.08-nominal_and_ordinal_variables.mkv
05.09-ordinal_encoding.mkv
05.10-one-hot_encoding_defined.mkv
05.11-one-hot_encoding.mkv
05.12-dummy_variable_encoding.mkv
05.13-ordinal_encoder_transform_on_breast_cancer_dataset.mkv
05.14-make_distributions_more_gaussian.mkv
05.15-power_transform_on_contrived_dataset.mkv
05.16-power_transform_on_sonar_dataset.mkv
05.17-box-cox_on_sonar_dataset.mkv
05.18-yeo-johnson_on_sonar_dataset.mkv
05.19-polynomial_features.mkv
05.20-effect_of_polynomial_degrees.mkv
Section 6
06.01-transforming_different_data_types.mkv
06.02-the_columntransformer.mkv
06.03-the_columntransformer_on_abalone_dataset.mkv
06.04-manually_transform_target_variable.mkv
06.05-automatically_transform_target_variable.mkv
06.06-challenge_of_preparing_new_data_for_a_model.mkv
06.07-save_model_and_data_scaler.mkv
06.08-load_and_apply_saved_scalers.mkv
Section 7
07.01-curse_of_dimensionality.mkv
07.02-techniques_for_dimensionality_reduction.mkv
07.03-linear_discriminant_analysis.mkv
07.04-linear_discriminant_analysis_demonstrated.mkv
07.05-principal_component_analysis.mkv
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