download скачать Free download скачать : Udemy Data Mining for Business Analytics Data Analysis in Python
mp4 | Video: h264,1280X720 | Audio: AAC, 44.1 KHz
Genre:eLearning | Language: English | Size:2.18 GB

Files Included :

001 Introduction to Data Mining course for Business Analytics & Data Analysis.mp4 (55.67 MB)
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003 Course Resources, Material, and Colab setup - Important!.mp4 (41.47 MB)
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004 How to get more from the course.mp4 (22.75 MB)
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005 Reviews and the future of the course.mp4 (32.37 MB)
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001 Game Plan for Survival Analysis section.mp4 (49.48 MB)
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002 Survival Analyisis Introduction.mp4 (15.53 MB)
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003 Case Study Briefing and Step by Step Guide.mp4 (3.52 MB)
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004 Python - Changing Directory.mp4 (10.59 MB)
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005 Python - Importing Libraries.mp4 (8.39 MB)
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006 Python - Loading Data.mp4 (13.79 MB)
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007 Python - Transforming Dependent Variable.mp4 (12.09 MB)
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008 Kaplan-Meyer Estimator.mp4 (5.9 MB)
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009 Censoring.mp4 (5.99 MB)
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010 Python - Kaplan-Meyer Estimator.mp4 (8.38 MB)
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011 Python - Calculating Specific Events.mp4 (30.81 MB)
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012 Python - Plotting Survival Curves.mp4 (5.66 MB)
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013 Python - Plotting Cumulative Curves.mp4 (11.87 MB)
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014 Log Rank Test.mp4 (2.86 MB)
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015 Python - Subsetting Dataframe.mp4 (3.69 MB)
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016 Python - Kaplan-Meyer Estimator per Gender.mp4 (9.9 MB)
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017 Python - Plotting both Survival Curves.mp4 (11.1 MB)
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018 Python - Log Rank Test.mp4 (8.79 MB)
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019 Extra Resources and Survival Analysis Challenge.mp4 (21.81 MB)
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020 Python - Survival Analysis Challenge Solutions.mp4 (37.42 MB)
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001 Game Plan.mp4 (4.84 MB)
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002 Cox Proportional Hazard Regression.mp4 (6.37 MB)
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003 Case Study Briefing and Step by Step Guide.mp4 (3.01 MB)
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004 Python - Preparing Script and Data.mp4 (46.09 MB)
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005 Python - Cox Proportional Hazard.mp4 (31.5 MB)
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006 Python - Regression Summary Visualization.mp4 (5.89 MB)
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007 Extra Resources and Challenge.mp4 (25.62 MB)
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008 Python - Solution Challenges.mp4 (37.33 MB)
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001 Game Plan.mp4 (7.44 MB)
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002 Case Study Briefing and Step by Step Guide.mp4 (4.52 MB)
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003 Problem Statement.mp4 (6 MB)
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004 Python - Installing libraries.mp4 (13.67 MB)
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005 Python - Importing Libraries and Data.mp4 (16.04 MB)
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006 Introducing CHAID.mp4 (7.78 MB)
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007 CHAID Statistics and Quirks.mp4 (9.7 MB)
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008 Python - Removing column and unique values check.mp4 (11.42 MB)
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009 Python - Visualizing Jobs Variable.mp4 (5.07 MB)
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010 Python - Transforming Jobs Variable.mp4 (15.18 MB)
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011 Python - Transforming Experience Variable.mp4 (11.62 MB)
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012 Python - Transform Minimum Variable.mp4 (14.48 MB)
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013 Python - Modify other variables to dummy variables.mp4 (3.01 MB)
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014 Python - CHAID Preparation.mp4 (5.64 MB)
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015 Python - CHAID Model.mp4 (25.54 MB)
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016 Python - Data Visualization with CHAID Model.mp4 (79.66 MB)
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017 Extra Resources and Challenge.mp4 (46.57 MB)
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018 Python - Challenge solutions.mp4 (51.68 MB)
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001 Game Plan.mp4 (4.46 MB)
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002 Case Study Briefing and Clustering.mp4 (14.32 MB)
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003 Gaussian Mixture Model vs  Kmeans.mp4 (11.66 MB)
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004 Python - Changing Directory and Importing Libraries.mp4 (8.4 MB)
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005 Python - Loading Data.mp4 (11.13 MB)
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006 AIC, BIC, and Step-by-Step Guide.mp4 (5.11 MB)
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007 Python - Optimal Clusters.mp4 (30.38 MB)
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008 Python - Gaussian Mixture Model.mp4 (3.89 MB)
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009 Python - Cluster Prediction.mp4 (18.56 MB)
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010 Python - Probability of belonging to each cluster.mp4 (20.33 MB)
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011 Python - Cluster Interpretation.mp4 (28.79 MB)
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012 Extra Resources and Challenge.mp4 (21.83 MB)
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013 Python - Challenge solutions.mp4 (27.82 MB)
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001 Game Plan.mp4 (4.79 MB)
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002 What is Dimension Reduction.mp4 (9.42 MB)
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003 Principal Component Analysis.mp4 (6.55 MB)
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004 Python - Importing Libraries.mp4 (7.78 MB)
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005 Python - Loading Data.mp4 (7.24 MB)
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006 Python - Transforming String Variables.mp4 (6.06 MB)
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007 Python - Correlation Matrix.mp4 (11.37 MB)
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008 Python - Standardizing Variables.mp4 (7.61 MB)
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009 Python - Optimal Number of Components.mp4 (12.7 MB)
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010 Python - Cumulative Explained Variance.mp4 (5.31 MB)
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011 Python - PCA.mp4 (8.16 MB)
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012 Python - PCA interpretation.mp4 (37.04 MB)
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013 Manifold Learning and t-SNE.mp4 (15.91 MB)
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014 Python - t-SNE.mp4 (6.34 MB)
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015 Python -Visualizing Manifold Learning.mp4 (16.54 MB)
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016 Extra Resources and Challenge.mp4 (20.08 MB)
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017 Python - Challenge Solutions.mp4 (88.46 MB)
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001 Game Plan.mp4 (3.08 MB)
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002 Step by Step Guide and Case Study Briefing.mp4 (4.67 MB)
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003 Python - Importing Libraries.mp4 (7.83 MB)
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004 Python - Loading Data.mp4 (6.12 MB)
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005 Association Rule Learning.mp4 (9.12 MB)
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006 Python - Create Transaction List.mp4 (28.36 MB)
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007 Python - Encoding Transactions.mp4 (22.72 MB)
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008 Apriori algorithm.mp4 (5.04 MB)
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009 Python - Association Rule Learning.mp4 (18.78 MB)
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010 Python - Apriori Visualization.mp4 (27.94 MB)
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011 Extra Resources and Challenge.mp4 (19.37 MB)
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012 Python - Challenge Solutions.mp4 (59.15 MB)
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001 Game Plan for Random Forest.mp4 (2.56 MB)
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002 Case Study Briefing and Step by Step Guide.mp4 (6.51 MB)
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003 Python - Importing Libraries.mp4 (7.75 MB)
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004 Python - Loading Data.mp4 (7 MB)
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005 Python - Transforming Categorical Variables.mp4 (4.62 MB)
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006 Random Forest.mp4 (10.19 MB)
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007 Python - Training and Test Set.mp4 (20.43 MB)
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008 Python - Random Forest.mp4 (7.65 MB)
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009 Confusion Matrix, AUC, and F1-Score.mp4 (12.6 MB)
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010 Python - Random Forest Predictions.mp4 (7.89 MB)
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011 Python - Classification Report.mp4 (18.06 MB)
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012 Python  - Feature Importance for Business Analytics.mp4 (13.45 MB)
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013 Extra Resources and Challenge.mp4 (32.7 MB)
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014 Python - Challenge Solutions.mp4 (33.42 MB)
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001 Game Plan for Explainable Artificial Intelligence.mp4 (2.38 MB)
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002 LIME.mp4 (9.32 MB)
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003 Python - Preparing LIME.mp4 (54.7 MB)
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004 Python - Explaining Predictions.mp4 (14.96 MB)
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005 Extra Resources and Challenge.mp4 (23.05 MB)
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006 Python - Challenge Solutions.mp4 (50.77 MB)
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001 Game Plan for XGBoost and SHAP.mp4 (2.83 MB)
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002 Case Study Briefing and Step by Step Guide.mp4 (3.22 MB)
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003 Python - Importing Libraries.mp4 (5.68 MB)
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004 Python - Loading Data.mp4 (15.34 MB)
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005 Introducing XGBoost.mp4 (5.38 MB)
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006 How XGBoost works part 1.mp4 (11.6 MB)
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007 How XGBoost works part 2.mp4 (6.08 MB)
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008 XGBoost quirks.mp4 (1.67 MB)
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009 Python - Isolate X and Y.mp4 (2.64 MB)
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010 Python - Training and Test Set.mp4 (4.7 MB)
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011 Python - XGBoost Matrices.mp4 (4.54 MB)
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012 XGBoost Parameters.mp4 (6.66 MB)
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013 Python - XGBoost Parameters.mp4 (7.18 MB)
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014 Python - XGBoost Model.mp4 (13.4 MB)
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015 Evaluate Regression-based Problems.mp4 (5.48 MB)
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016 Python - Predictions.mp4 (2.48 MB)
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017 Python - MAE and RSME.mp4 (12.61 MB)
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018 SHAP.mp4 (8.17 MB)
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019 Python - Preparing SHAP.mp4 (2.4 MB)
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020 Python - Local Interpretability.mp4 (27.06 MB)
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021 Python - Dependency Plots.mp4 (11.23 MB)
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022 Python - Global Interpretability.mp4 (4.89 MB)
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023 Extra Resources and Challenge.mp4 (16.51 MB)
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024 Python - Challenge Solutions.mp4 (64.81 MB)
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