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Language:
English
Total Size:
2.0 GB
Info Hash:
BBF56A2A8E04C6E70C8E858E45AD7FD39389B6A0
Added By:
Added:
May 1, 2025, 8:25 a.m.
Stats:
|
(Last updated: May 16, 2025, 6:32 p.m.)
| File | Size |
|---|---|
| Get Bonus Downloads Here.url | 183 bytes |
| 1 -Intro.pptx | 289.8 KB |
| 1 -Introduction.mp4 | 30.2 MB |
| 1 -Segmentation_Steps (1).ipynb | 2.0 MB |
| 1 -Webscraping_Performance_Metrics (1).ipynb | 26.8 KB |
| 1 -bigquery_code.sql | 6.6 KB |
| 1 -sas_code.sas | 12.4 KB |
| 2 -Business Problem.mp4 | 7.1 MB |
| 2 -Business_Problem_Store_Segmentation.pdf | 1.8 KB |
| 3 -Variables CU.pptx | 1.2 MB |
| 3 -Variables.mp4 | 14.0 MB |
| 1 -Idea Decision Tree Feature Importance to Explain Membership to a Cluster.mp4 | 19.8 MB |
| 1 -cluster_tree_profiling.pdf | 28.7 KB |
| 2 -Function to plot distribution for a given variable (cluster vs population).mp4 | 28.5 MB |
| 2 -plot_segment_vs_population_distribution.pdf | 32.9 KB |
| 3 -Increasing the number of variables appearing in feature importance.mp4 | 37.4 MB |
| 3 -tree_feature_importance_methods.pdf | 42.1 KB |
| 4 -A robust method to choose top feature importances along several random states.mp4 | 58.0 MB |
| 4 -robust_feature_importance_per_cluster.pdf | 36.1 KB |
| 5 -Interpretation of segment 1.mp4 | 24.7 MB |
| 5 -Segment_1_Analysis_Complete.pdf | 640.4 KB |
| 6 -Interpretation of segment 2.mp4 | 15.0 MB |
| 6 -Segment_2_Analysis_Complete.pdf | 821.8 KB |
| 7 -Interpretation of segment 3.mp4 | 12.9 MB |
| 7 -Segment_3_Analysis_Complete.pdf | 477.8 KB |
| 8 -Interpretation of segment 4.mp4 | 11.7 MB |
| 8 -Segment_4_Analysis_Complete.pdf | 737.4 KB |
| 1 -Final Results.pptx | 2.2 MB |
| 1 -Overview of the 4 segments.mp4 | 30.6 MB |
| 1 -Step 1- preparing_data_presentation.pdf | 43.2 KB |
| 1 -Step 2 distribution_life_cycle_plot.pdf | 40.6 KB |
| 1 -Step 3 pie_chart_gender_segment_vs_population.pdf | 37.8 KB |
| 1 -Step 4 distribution_plot_weather_segment_vs_population.pdf | 39.4 KB |
| 1 -Step 5 preprocess_radar_chart_data.pdf | 38.1 KB |
| 1 -Step 6 section_contribution_segment_vs_population.pdf | 48.9 KB |
| 1 -metricas_x_segmento escalado.xlsx | 15.2 KB |
| 1 -participacion_seccion_x_segmento.xlsx | 12.5 KB |
| 2 -Segment 1 Tech-Focused Small Stores.mp4 | 34.1 MB |
| 3 -Segment 2 Electronics & Furniture for Seniors.mp4 | 13.4 MB |
| 4 -Segment 3 Comfort-Oriented Family stores.mp4 | 11.4 MB |
| 5 -Segment 4 Single-Customer budget Stores.mp4 | 8.1 MB |
| 6 -Comment On Cumulative Profit and Turnover.mp4 | 7.6 MB |
| 1 -Colab Connection to BQ (Extraction of Stores).mp4 | 26.1 MB |
| 1 -colab connection.pdf | 25.3 KB |
| 10 -Google Sheet (Stores Size) + Simple Preprocessing Processing.mp4 | 28.4 MB |
| 10 -size_of_stores.pdf | 25.2 KB |
| 11 -API Denue (Competition Around Stores).mp4 | 108.8 MB |
| 11 -extracting_city_competition.pdf | 44.2 KB |
| 2 -BigQuery Transactions.mp4 | 37.1 MB |
| 2 -transactions_from_bigquery.pdf | 34.7 KB |
| 3 -Existing Customer Segmentation.mp4 | 34.9 MB |
| 3 -existing customer segmentation.pdf | 43.4 KB |
| 4 -Webscraping.mp4 | 128.6 MB |
| 4 -webscraping performance metrics.pdf | 45.9 KB |
| 5 -Some Preprocessing On Output of Webscraping.mp4 | 13.7 MB |
| 5 -some_preprocessing.pdf | 22.1 KB |
| 6 -More Preprocessing On Output of Webscraping.mp4 | 38.1 MB |
| 6 -more_preprocessing.pdf | 24.5 KB |
| 7 -Cumulative Performance Metrics from Webscraping.mp4 | 46.8 MB |
| 7 -more preprocesing cumulative metrics.pdf | 39.3 KB |
| 8 -Economy of the City (BQ) + Some Preprocessing.mp4 | 32.7 MB |
| 8 -environment_city_economy.pdf | 19.6 KB |
| 9 -Weather (BQ) + Some Preprocessing.mp4 | 9.5 MB |
| 9 -weather extraction.pdf | 19.1 KB |
| 1 -Missing Values Due to Opening Dates.mp4 | 40.4 MB |
| 1 -filter store and sections.pdf | 276.6 KB |
| 2 -Intersecting Tables and Dataframes with Selected Stores and Sections.mp4 | 42.4 MB |
| 2 -intersecting with relevant stores and sections.pdf | 31.1 KB |
| 3 -Missing Values in Transactions Table.mp4 | 53.2 MB |
| 3 -missing values in transactions.pdf | 356.5 KB |
| 1 -Contribution of Sales per Section.mp4 | 24.2 MB |
| 1 -sales_per_section_percentage_contribution.pdf | 25.2 KB |
| 2 -Contribution per Life Cycle.mp4 | 19.1 MB |
| 2 -life_cycle_contribution.pdf | 21.1 KB |
| 3 -Contribution per Gender.mp4 | 8.8 MB |
| 3 -gender_contribution.pdf | 19.7 KB |
| 4 -Average Sales, Profit and Inventory.mp4 | 50.7 MB |
| 4 -monthly_averages_inventory_profit_sales.pdf | 23.8 KB |
| 5 -Cumulative Turnover and Cumulative Profit.mp4 | 12.1 MB |
| 5 -cumulative_performance_metrics.pdf | 28.8 KB |
| 6 -Average Ticket, Average Spending and Average Credit Limit.mp4 | 10.5 MB |
| 6 -gasto_ticket_lc_promedio_code.pdf | 355.0 KB |
| 1 -Top sections contributing to the total sales.mp4 | 31.6 MB |
| 1 -top_sections.pdf | 23.9 KB |
| 2 -Correlation Plots.mp4 | 49.2 MB |
| 2 -correlation_plots.pdf | 24.1 KB |
| 3 -Distribution Plots.mp4 | 73.3 MB |
| 3 -distribution_plots.pdf | 39.9 KB |
| 4 -Box plots.mp4 | 28.7 MB |
| 4 -box_plots.pdf | 27.0 KB |
| 1 -Winsorization, Yeo-Johnson Transformation and Standardization.mp4 | 35.3 MB |
| 1 -data_transformation_functions.pdf | 21.8 KB |
| 1 -transformations.pptx | 1.2 MB |
| 2 -Transforming Top Sections.mp4 | 36.2 MB |
| 2 -transform_top_sections.pdf | 25.4 KB |
| 3 -Transforming Weather Variable.mp4 | 9.5 MB |
| 3 -transform_weather.pdf | 21.8 KB |
| 4 -Transforming Customer Variables.mp4 | 18.0 MB |
| 4 -transform_customers.pdf | 23.4 KB |
| 5 -Transforming Economy Variables.mp4 | 12.0 MB |
| 5 -transform_environment_economy.pdf | 23.4 KB |
| 6 -Transforming Performance Variables and Merge Everything.mp4 | 45.7 MB |
| 6 -transform_performance_metrics.pdf | 26.9 KB |
| 1 -PCA Coefficients of First Component.mp4 | 38.0 MB |
| 1 -pca_python_code.pdf | 19.7 KB |
| 2 -PCA Interpreting Coefficients of First Component.mp4 | 35.6 MB |
| 2 -pca_component1_interpretation.pdf | 575.8 KB |
| 3 -PCA Interpreting Coefficients Second Component.mp4 | 15.3 MB |
| 3 -pca_component2_interpretation.pdf | 568.1 KB |
| 4 -PCA Interpreting Coefficients Third Component.mp4 | 20.7 MB |
| 4 -pca_component3_interpretation.pdf | 364.1 KB |
| 5 -PCA Interpreting Coefficients of Components Fourth, Fifth and Sixth.mp4 | 20.7 MB |
| 5 -pca_component4_interpretation.pdf | 366.2 KB |
| 5 -pca_component5_interpretation.pdf | 374.2 KB |
| 5 -pca_component6_interpretation.pdf | 552.4 KB |
| 1 -Elbow Method.mp4 | 23.3 MB |
| 1 -Elbow Method.pdf | 495.7 KB |
| 2 -Jaccard Similarity To Compare Different Cluster Labels.mp4 | 22.2 MB |
| 2 -jarccard similarity.pdf | 357.1 KB |
| 3 -Two Auxiliary Functions.mp4 | 6.4 MB |
| 3 -two_auxiliary_functions.pdf | 33.5 KB |
| 4 -Detecting Random State of the Most Stable Clustering.mp4 | 26.3 MB |
| 4 -detect_stable_clustering.pdf | 492.2 KB |
| 5 -Fitting K Means With Selected Random State.mp4 | 32.8 MB |
| 5 -fit k means with selected random state.pdf | 27.4 KB |
| 6 -Evaluate Clustering with Silhouette Score.mp4 | 26.9 MB |
| 6 -silhouette_score.pdf | 41.4 KB |
| 1 -(Optional) SAS - BigQuery Connection.mp4 | 40.7 MB |
| 1 -sas_connection_bigquery.pdf | 57.6 KB |
| 2 -(Optional) SAS Miner Diagram.mp4 | 50.3 MB |
| 3 -SAS Miner Profiling.mp4 | 67.2 MB |
| 3 -feature importance decision tree for segment.pdf | 43.5 KB |
| 4 -Interpretation of segments (SAS Miner Profiling).mp4 | 103.7 MB |
| 4 -profiling_segments.pdf | 1014.3 KB |
| 5 -(Optional) Extraction of SAS Miner Clustering Code.mp4 | 23.9 MB |
| 5 -scoring_code_sas_miner.pdf | 54.6 KB |
| 5 -scoring_sas.txt | 10.7 KB |
| Bonus Resources.txt | 70 bytes |
Name
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Uploader
Size
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345.1 MB
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2023-10-24
| Uploaded by freecoursewb | Size 345.1 MB | Health [ 0 /0 ] | Added 2023-10-24 |
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621.2 MB
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2023-10-23
| Uploaded by freecoursewb | Size 621.2 MB | Health [ 0 /3 ] | Added 2023-10-23 |
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646.6 MB
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2023-10-05
| Uploaded by FreeCourseWeb | Size 646.6 MB | Health [ 7 /3 ] | Added 2023-10-05 |
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176.0 MB
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2023-07-01
| Uploaded by FreeCourseWeb | Size 176.0 MB | Health [ 0 /1 ] | Added 2023-07-01 |
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578.0 MB
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2023-06-01
| Uploaded by freecoursewb | Size 578.0 MB | Health [ 0 /2 ] | Added 2023-06-01 |
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2.0 GB
[14
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2025-05-01
| Uploaded by freecoursewb | Size 2.0 GB | Health [ 14 /18 ] | Added 2025-05-01 |
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SOURCE: Udemy Using Data Science for Retail Store Segmentation
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