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1. Game Plan.mp4 |
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1. Introduction.mp4 |
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1. Where you could skill up next....html |
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10. Python - Apriori Visualization.mp4 |
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10. Python - Calculating Specific Events.mp4 |
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10. Python - Cumulative Explained Variance.mp4 |
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10. Python - Probability of belonging to each cluster.mp4 |
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10. Python - Probability of belonging to each cluster.srt |
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10. Python - Random Forest Predictions.mp4 |
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10. Python - Random Forest Predictions.srt |
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10. Python - Training and Test Set.mp4 |
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10. Python - Training and Test Set.srt |
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10. Python - Transforming Jobs Variable.mp4 |
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11. Extra Resources and Challenge.mp4 |
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11. Python - Classification Report.mp4 |
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11. Python - Cluster Interpretation.mp4 |
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11. Python - Cluster Interpretation.srt |
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11. Python - PCA.mp4 |
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11. Python - PCA.srt |
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11. Python - Plotting Survival Curves.mp4 |
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11. Python - Transforming Experience Variable.mp4 |
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11. Python - Transforming Experience Variable.srt |
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11. Python - XGBoost Matrices.mp4 |
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12. Extra Resources and Challenge.mp4 |
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12. Python .- Feature Importance.mp4 |
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12. Python .- Feature Importance.srt |
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12. Python - Challenge Solutions.mp4 |
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12. Python - Challenge Solutions.srt |
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12. Python - PCA interpretation.mp4 |
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12. Python - PCA interpretation.srt |
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12. Python - Plotting Cumulative Curves.mp4 |
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12. Python - Transform Minimum Variable.mp4 |
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12. Python - Transform Minimum Variable.srt |
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12. XGBoost Parameters.mp4 |
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12. XGBoost Parameters.srt |
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13. Extra Resources and Challenge.mp4 |
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13. Log Rank Test.mp4 |
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13. Manifold Learning and t-SNE.mp4 |
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13. Manifold Learning and t-SNE.srt |
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13. Python - Challenge solutions.mp4 |
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13. Python - Challenge solutions.srt |
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13. Python - Modify other variables to dummy variables.mp4 |
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13. Python - Modify other variables to dummy variables.srt |
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13. Python - XGBoost Parameters.mp4 |
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13. Python - XGBoost Parameters.srt |
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14. Python - CHAID Preparation.mp4 |
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14. Python - Challenge Solutions.mp4 |
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14. Python - Subsetting Dataframe.mp4 |
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14. Python - t-SNE.mp4 |
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14. Python - XGBoost Model.mp4 |
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15. Evaluate Regression-based Problems.mp4 |
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15. Python - CHAID Model.mp4 |
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15. Python - CHAID Model.srt |
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15. Python - Plotting both Survival Curves.mp4 |
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15. Python - Plotting both Survival Curves.srt |
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15. Python -Visualizing Manifold Learning.mp4 |
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15. Python -Visualizing Manifold Learning.srt |
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16. Extra Resources and Challenge.mp4 |
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16. Extra Resources and Challenge.srt |
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16. Python - Log Rank Test.mp4 |
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16. Python - Log Rank Test.srt |
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16. Python - Predictions.mp4 |
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16. Python - Visualizing CHAID Model.mp4 |
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17. Extra Resources and Challenge.mp4 |
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17. Python - Challenge Solutions.mp4 |
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17. Python - Kaplan-Meyer Estimator per Gender.mp4 |
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17. Python - Kaplan-Meyer Estimator per Gender.srt |
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17. Python - MAE and RSME.mp4 |
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18. Extra Resources and Survival Analysis Challenge.mp4 |
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18. Extra Resources and Survival Analysis Challenge.srt |
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18. Python - Challenge solutions.mp4 |
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18. SHAP.mp4 |
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18. SHAP.srt |
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19. Python - Preparing SHAP.mp4 |
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19. Python - Preparing SHAP.srt |
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19. Python - Survival Analysis Challenge Solutions.mp4 |
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19. Python - Survival Analysis Challenge Solutions.srt |
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2. Case Study Briefing and Clustering.mp4 |
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2. Case Study Briefing and Clustering.srt |
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2. Case Study Briefing and Step by Step Guide.mp4 |
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2. Case Study Briefing and Step by Step Guide.mp4 |
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2. Cox Proportional Hazard Regression.mp4 |
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2. Cox Proportional Hazard Regression.srt |
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2. Knowledge Requirements.mp4 |
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2. Knowledge Requirements.srt |
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2. LIME.mp4 |
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2. LIME.srt |
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2. Step by Step Guide and Case Study Briefing.mp4 |
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2. Survival Analyisis Introduction.mp4 |
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2. Survival Analyisis Introduction.srt |
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2. What is Dimension Reduction.mp4 |
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2. What is Dimension Reduction.srt |
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20. Python - Local Interpretability.mp4 |
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20. Python - Local Interpretability.srt |
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21. Python - Dependency Plots.mp4 |
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21. Python - Dependency Plots.srt |
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22. Python - Global Interpretability.mp4 |
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22. Python - Global Interpretability.srt |
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23. Extra Resources and Challenge.mp4 |
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24. Python - Challenge Solutions.mp4 |
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3. Case Study Briefing and Step by Step Guide.mp4 |
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3. Case Study Briefing and Step by Step Guide.srt |
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3. Gaussian Mixture Model vs. Kmeans.mp4 |
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3. Gaussian Mixture Model vs. Kmeans.srt |
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3. Principal Component Analysis.mp4 |
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3. Principal Component Analysis.srt |
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3. Problem Statement.mp4 |
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3. Problem Statement.srt |
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3. Python - Importing Libraries.mp4 |
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3. Python - Importing Libraries.mp4 |
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3. Python - Importing Libraries.mp4 |
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3. Python - Importing Libraries.srt |
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3. Python - Importing Libraries.srt |
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3. Python - Preparing LIME.mp4 |
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3. Python - Preparing LIME.srt |
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3. Your resources.html |
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4. Course Resources, Material, and Colab setup - Important!.mp4 |
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4. Course Resources, Material, and Colab setup - Important!.srt |
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4. Python - Changing Directory and Importing Libraries.mp4 |
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4. Python - Changing Directory and Importing Libraries.srt |
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4. Python - Explaining Predictions.mp4 |
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4. Python - Importing Libraries.mp4 |
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4. Python - Importing Libraries.mp4 |
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4. Python - Importing Libraries.srt |
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4. Python - Installing libraries.mp4 |
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4. Python - Loading Data.mp4 |
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4. Python - Loading Data.mp4 |
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4. Python - Loading Data.srt |
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4. Python - Preparing Script and Data.mp4 |
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5. Association Rule Learning.mp4 |
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5. Extra Resources and Challenge.mp4 |
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5. Extra Resources and Challenge.srt |
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5. Introducing XGBoost.mp4 |
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5. Let's connect!.html |
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5. Python - Cox Proportional Hazard.mp4 |
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5. Python - Importing Libraries and Data.mp4 |
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5. Python - Importing Libraries and Data.srt |
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5. Python - Loading Data.mp4 |
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5. Python - Transforming Categorical Variables.mp4 |
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6. AIC, BIC, and Step-by-Step Guide.mp4 |
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6. How XGBoost works part 1.mp4 |
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6. Introducing CHAID.mp4 |
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6. Introducing CHAID.srt |
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6. Python - Challenge Solutions.mp4 |
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6. Python - Create Transaction List.mp4 |
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6. Python - Regression Summary Visualization.mp4 |
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6. Python - Transforming Dependent Variable.mp4 |
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6. Python - Transforming String Variables.mp4 |
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6. Random Forest.mp4 |
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6. Random Forest.srt |
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7. CHAID Statistics and Quirks.mp4 |
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7. Extra Resources and Challenge.mp4 |
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7. How XGBoost works part 2.mp4 |
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7. Kaplan-Meyer Estimator.mp4 |
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7. Kaplan-Meyer Estimator.srt |
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7. Python - Correlation Matrix.mp4 |
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7. Python - Correlation Matrix.srt |
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7. Python - Encoding Transactions.mp4 |
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7. Python - Encoding Transactions.srt |
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7. Python - Optimal Clusters.mp4 |
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7. Python - Optimal Clusters.srt |
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7. Python - Training and Test Set.mp4 |
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8. Apriori algorithm.mp4 |
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8. Censoring.mp4 |
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8. Censoring.srt |
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8. Python - Gaussian Mixture Model.mp4 |
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8. Python - Gaussian Mixture Model.srt |
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8. Python - Random Forest.mp4 |
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8. Python - Random Forest.srt |
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8. Python - Removing column and unique values check.mp4 |
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8. Python - Solution Challenges.mp4 |
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8. Python - Standardizing Variables.mp4 |
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8. Python - Standardizing Variables.srt |
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8. XGBoost quirks.mp4 |
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8. XGBoost quirks.srt |
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9. Confusion Matrix, AUC, and F1-Score.mp4 |
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9. Confusion Matrix, AUC, and F1-Score.srt |
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9. Python - Association Rule Learning.mp4 |
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9. Python - Association Rule Learning.srt |
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9. Python - Cluster Prediction.mp4 |
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9. Python - Isolate X and Y.mp4 |
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9. Python - Kaplan-Meyer Estimator.mp4 |
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9. Python - Optimal Number of Components.mp4 |
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9. Python - Visualizing Jobs Variable.mp4 |
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TutsNode.com.txt |
63б |