[GigaCourse.Com] Udemy - Business Data Analytics & Intelligence with Python 2023
File List
- 9. Google Causal Impact (Econometrics and Causal Inference)/22. CHALLENGE Solutions.mp4 164.4 MB
- 13. Gaussian Mixture/14. CHALLENGE Solutions.mp4 160.6 MB
- 16. Facebook Prophet/33. CHALLENGE Solutions (Part 3).mp4 127.8 MB
- 16. Facebook Prophet/32. CHALLENGE Solutions (Part 2).mp4 111.6 MB
- 6. Multilinear Regression/22. CHALLENGE Solutions.mp4 110.6 MB
- 10. Matching/24. CHALLENGE Solutions.mp4 107.5 MB
- 7. Logistic Regression/20. CHALLENGE Solutions.mp4 90.6 MB
- 13. Gaussian Mixture/12. Python - Interpretation.mp4 78.7 MB
- 1. Introduction/3. Join Our Online Classroom!.mp4 75.3 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/16. Python - Correlation Matrix and Heatmap.mp4 74.3 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/18. CHALLENGE Solutions.mp4 72.6 MB
- 16. Facebook Prophet/31. CHALLENGE Solutions (Part 1).mp4 69.2 MB
- 10. Matching/13. Python - Transforming Race Variable.mp4 66.2 MB
- 4. Intermediary Statistics/20. Python - T-test.mp4 65.5 MB
- 16. Facebook Prophet/17. Python - Facebook Prophet.mp4 61.0 MB
- 16. Facebook Prophet/28. Python - Parameter Tuning.mp4 60.9 MB
- 16. Facebook Prophet/20. Python - Event Assessment.mp4 60.3 MB
- 3. Basic Statistics/5. Python - Mean.mp4 59.7 MB
- 15. Random Forest/21. CHALLENGE Solutions (Part 2).mp4 59.1 MB
- 1. Introduction/5. Setting up the Course Material.mp4 58.0 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/15. Python - Stationarity.mp4 57.9 MB
- 16. Facebook Prophet/19. Python - Forecasting.mp4 57.7 MB
- 7. Logistic Regression/13. Python - Function to Read Coefficients.mp4 56.7 MB
- 10. Matching/21. Python - Matching Robustness Repeated Samples.mp4 56.2 MB
- 16. Facebook Prophet/24. Python - Cross-Validation.mp4 56.0 MB
- 15. Random Forest/20. CHALLENGE Solutions (Part 1).mp4 55.9 MB
- 3. Basic Statistics/13. Python - Correlation.mp4 54.0 MB
- 1. Introduction/1. Python for Business Analytics & Intelligence.mp4 53.6 MB
- 3. Basic Statistics/4. Python - Directory, Libraries and Data.mp4 51.3 MB
- 4. Intermediary Statistics/9. Python - Shapiro-Wilks Test.mp4 51.1 MB
- 4. Intermediary Statistics/23. Python - Chi-square test.mp4 50.5 MB
- 10. Matching/19. Python - Matching Model.mp4 50.2 MB
- 7. Logistic Regression/6. Python - Histogram and Outlier Removal.mp4 48.2 MB
- 15. Random Forest/18. Python - Parameter Tuning.mp4 48.1 MB
- 16. Facebook Prophet/22. Python - Visualization.mp4 47.9 MB
- 10. Matching/9. Python - T-Test Loop.mp4 47.3 MB
- 16. Facebook Prophet/25. Python - Cross-Validation Results and Visualization.mp4 46.2 MB
- 4. Intermediary Statistics/16. Python - Confidence Interval.mp4 45.8 MB
- 1. Introduction/7. ZTM Resources.mp4 44.6 MB
- 4. Intermediary Statistics/15. Confidence interval.mp4 43.0 MB
- 6. Multilinear Regression/17. Python - Multilinear Regression.mp4 42.8 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/20. Python - Causal Impact Results.mp4 41.8 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/12. Python - Quartiles.mp4 41.8 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/9. Python - Load Bitcoin Price Data.mp4 41.1 MB
- 4. Intermediary Statistics/5. Python - Normal Distribution Visualization.mp4 40.9 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/21. CHALLENGE Introduction.mp4 40.6 MB
- 6. Multilinear Regression/7. Python - Plotting Continuous Variables.mp4 39.4 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/23. EXERCISE Imposter Syndrome.mp4 39.2 MB
- 13. Gaussian Mixture/9. Python - Optimal Number of Clusters.mp4 38.8 MB
- 7. Logistic Regression/17. Python - Manual Accuracy Assessment.mp4 38.4 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/12. Python - Data Preparation.mp4 38.3 MB
- 10. Matching/14. Python - Transforming Education Variable.mp4 38.1 MB
- 6. Multilinear Regression/20. Python - Accuracy Assessment.mp4 37.5 MB
- 16. Facebook Prophet/11. Python - Black Friday Holiday.mp4 37.5 MB
- 16. Facebook Prophet/29. Python - Parameter Tuning Results.mp4 36.8 MB
- 5. Linear Regression/12. EXERCISE Python - Linear Regression.mp4 36.0 MB
- 10. Matching/8. Python - T-Test.mp4 35.4 MB
- 10. Matching/23. CHALLENGE Introduction.mp4 34.3 MB
- 16. Facebook Prophet/27. Python - Parameter Grid.mp4 34.1 MB
- 5. Linear Regression/7. Linear Regression Output.mp4 33.4 MB
- 10. Matching/18. Python - Plotting Common Support Region.mp4 33.0 MB
- 13. Gaussian Mixture/13. CHALLENGE Introduction.mp4 32.9 MB
- 6. Multilinear Regression/4. Python - Preparing Script and Loading Data.mp4 32.9 MB
- 16. Facebook Prophet/6. Python - Loading and Inspecting the Data.mp4 32.6 MB
- 4. Intermediary Statistics/21. EXERCISE Python - T-test.mp4 31.9 MB
- 15. Random Forest/11. Python - Training and Test Set.mp4 31.6 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/18. Python - Google Causal Impact.mp4 31.1 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/9. Python - Customer Level Aggregation.mp4 30.4 MB
- 7. Logistic Regression/16. Python - Confusion Matrix.mp4 29.6 MB
- 10. Matching/16. Common Support Region.mp4 29.5 MB
- 3. Basic Statistics/12. Correlation.mp4 29.4 MB
- 16. Facebook Prophet/18. Python - Regressor Coefficients.mp4 29.3 MB
- 16. Facebook Prophet/21. Python - Accuracy Assessment.mp4 29.3 MB
- 7. Logistic Regression/19. CHALLENGE Introduction.mp4 29.3 MB
- 15. Random Forest/19. CHALLENGE Introduction.mp4 29.1 MB
- 10. Matching/11. Python - Chi-square Loop.mp4 29.0 MB
- 4. Intermediary Statistics/12. Python - Standard Error.mp4 28.8 MB
- 4. Intermediary Statistics/4. Python - Preparing Script and Loading Data.mp4 28.6 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/8. Python - Dates.mp4 28.4 MB
- 4. Intermediary Statistics/6. EXERCISE Python - Normal Distribution.mp4 28.3 MB
- 6. Multilinear Regression/10. Python - For Loop.mp4 28.2 MB
- 7. Logistic Regression/5. Python - Summary Statistics.mp4 27.9 MB
- 7. Logistic Regression/4. Python - Preparing Script and Loading Data.mp4 27.8 MB
- 6. Multilinear Regression/21. CHALLENGE Introduction.mp4 27.7 MB
- 5. Linear Regression/4. Python - Preparing Script and Loading Data.mp4 27.5 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/16. Python - Results Summary.mp4 27.3 MB
- 4. Intermediary Statistics/7. P-value.mp4 27.3 MB
- 10. Matching/5. Python - Loading Data.mp4 27.2 MB
- 6. Multilinear Regression/9. Python - Categorical Variables.mp4 26.5 MB
- 10. Matching/17. Python - Logistic Regression for Common Support Region.mp4 26.3 MB
- 5. Linear Regression/9. Python - Plotting Regression.mp4 26.1 MB
- 15. Random Forest/15. Python - Feature Importance.mp4 26.1 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/19. Interpreting the Causal Impact Plots.mp4 25.6 MB
- 3. Basic Statistics/8. Python - Median.mp4 25.4 MB
- 15. Random Forest/14. Python - Classification Report and F1 score.mp4 24.7 MB
- 7. Logistic Regression/15. Confusion Matrix.mp4 24.5 MB
- 3. Basic Statistics/14. EXERCISE Python - Correlation.mp4 24.1 MB
- 15. Random Forest/8. Python - Summary Statistics.mp4 23.6 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/6. Python - Loading Data.mp4 23.5 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/11. Python - Loading More Stock Data.mp4 23.3 MB
- 10. Matching/10. Python - Chi-square Test.mp4 23.2 MB
- 10. Matching/4. Python - Libraries and Directory.mp4 22.8 MB
- 4. Intermediary Statistics/24. EXERCISE Python - Chi-square.mp4 22.7 MB
- 16. Facebook Prophet/10. Python - Easter Holiday.mp4 22.5 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/14. Python - RFM Function.mp4 22.4 MB
- 5. Linear Regression/8. Python - Linear Regression model and summary.mp4 21.9 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/8. Python - Date Variable.mp4 21.8 MB
- 7. Logistic Regression/10. Python - Training and Test Set.mp4 21.6 MB
- 7. Logistic Regression/14. Python - Predictions.mp4 21.3 MB
- 6. Multilinear Regression/8. Python - Correlation Matrix.mp4 21.1 MB
- 6. Multilinear Regression/12. Python - Isolate X and Y.mp4 20.7 MB
- 3. Basic Statistics/9. EXERCISE Python - Median.mp4 20.3 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/7. Python - Libraries and Dates.mp4 20.1 MB
- 15. Random Forest/6. Python - Loading Data.mp4 19.7 MB
- 10. Matching/22. Python - Removing 1 Confounder.mp4 19.6 MB
- 7. Logistic Regression/18. Python - Classification Report.mp4 19.6 MB
- 1. Introduction/6. The Modern Day Business Analyst.mp4 19.5 MB
- 3. Basic Statistics/10. Python - Mode.mp4 18.8 MB
- 6. Multilinear Regression/5. Python - Summary Statistics.mp4 18.8 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/11. Python - Tidying up Dataframe.mp4 18.7 MB
- 7. Logistic Regression/12. Python - Logistic Regression.mp4 18.6 MB
- 10. Matching/2. Matching.mp4 18.6 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/1. Why Econometrics and Causal Inference.mp4 18.3 MB
- 16. Facebook Prophet/7. Python - Transforming Date Variable.mp4 18.0 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/17. CHALLENGE Introduction.mp4 17.9 MB
- 5. Linear Regression/11. Python - Dummy Variable.mp4 17.8 MB
- 15. Random Forest/12. Python - Random Forest Model.mp4 17.8 MB
- 15. Random Forest/17. Python - Parameter Grid.mp4 17.7 MB
- 3. Basic Statistics/16. Python - Standard Deviation.mp4 17.7 MB
- 6. Multilinear Regression/11. Python - Creating Dummy Variables.mp4 17.6 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/14. Correlation Recap and Stationarity.mp4 17.3 MB
- 7. Logistic Regression/8. Python - Transforming Dependent Variable.mp4 17.3 MB
- 15. Random Forest/3. How Decision Trees Work.mp4 17.3 MB
- 10. Matching/15. Python - Cleaning and Preparing Dataframe.mp4 17.2 MB
- 17. Where To Go From Here/1. Thank You!.mp4 16.9 MB
- 10. Matching/7. Python - Comparing Means per Group.mp4 16.7 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/10. Assumptions.mp4 16.6 MB
- 13. Gaussian Mixture/6. Python - Load Data.mp4 16.6 MB
- 16. Facebook Prophet/30. CHALLENGE Introduction - Demand in NYC.mp4 16.6 MB
- 3. Basic Statistics/6. EXERCISE Python - Mean.mp4 16.5 MB
- 5. Linear Regression/3. Linear Regression.mp4 16.2 MB
- 4. Intermediary Statistics/17. EXERCISE Python - Confidence Interval.mp4 16.2 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/7. Python - Creating Sales Variable.mp4 16.1 MB
- 4. Intermediary Statistics/25. Powerposing and p-hacking.mp4 15.7 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/15. Python - Applying RFM Function.mp4 15.7 MB
- 16. Facebook Prophet/34. Forecasting at Uber.mp4 15.6 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/13. Python - Training Dataframe.mp4 15.5 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/17. Python - Google Causal Impact Setup.mp4 15.2 MB
- 16. Facebook Prophet/5. Python - Directory and Libraries.mp4 15.1 MB
- 7. Logistic Regression/7. Python - Correlation Matrix.mp4 15.1 MB
- 4. Intermediary Statistics/10. EXERCISE Python - Shapiro-Wilks.mp4 15.1 MB
- 13. Gaussian Mixture/5. Python - Directory and Data.mp4 14.7 MB
- 6. Multilinear Regression/18. Accuracy KPIs (Key Performance Indicators).mp4 14.5 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/3. RFM Model.mp4 14.4 MB
- 13. Gaussian Mixture/11. Python - Cluster Prediction and Assignment.mp4 14.3 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/4. CASE STUDY Bitcoin and PayPal (Briefing).mp4 14.3 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/5. Python - Directory and Libraries.mp4 14.3 MB
- 15. Random Forest/5. Python - Directory and Libraries.mp4 14.0 MB
- 6. Multilinear Regression/16. Python - Train and Test Split.mp4 13.9 MB
- 13. Gaussian Mixture/3. Gaussian Mixture Model.mp4 13.8 MB
- 15. Random Forest/7. Python - Transform Object into Numerical Variables.mp4 13.5 MB
- 15. Random Forest/10. Python - Isolate X and Y.mp4 13.1 MB
- 13. Gaussian Mixture/15. My Experience with Segmentation.mp4 13.0 MB
- 4. Intermediary Statistics/2. Normal Distribution.mp4 12.8 MB
- 3. Basic Statistics/11. EXERCISE Python - Mode.mp4 12.6 MB
- 4. Intermediary Statistics/13. EXERCISE Python - Standard Error.mp4 12.6 MB
- 3. Basic Statistics/18. CASE STUDY Moneyball.mp4 12.5 MB
- 10. Matching/6. Unconfoundedness.mp4 12.2 MB
- 5. Linear Regression/10. Dummy Variable Trap.mp4 12.1 MB
- 16. Facebook Prophet/3. Facebook Prophet.mp4 12.1 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/13. Python - RFM Score.mp4 12.0 MB
- 13. Gaussian Mixture/7. Python - Transform Character variables.mp4 12.0 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/5. Difference-in-Differences Framework.mp4 11.6 MB
- 7. Logistic Regression/9. Python - Prepare X and Y.mp4 11.5 MB
- 5. Linear Regression/6. Python - Adding Constant.mp4 11.5 MB
- 5. Linear Regression/5. Python - Isolate X and Y.mp4 11.0 MB
- 7. Logistic Regression/11. How to Read Logistic Regression Coefficients.mp4 10.9 MB
- 16. Facebook Prophet/15. Facebook Prophet Model.mp4 10.8 MB
- 16. Facebook Prophet/14. Python - Training and Test Set.mp4 10.7 MB
- 13. Gaussian Mixture/8. AIC and BIC.mp4 10.1 MB
- 16. Facebook Prophet/16. Additive vs. Multiplicative Seasonality.mp4 10.1 MB
- 7. Logistic Regression/3. Logistic Regression.mp4 10.1 MB
- 4. Intermediary Statistics/3. CASE STUDY Wine Quality (Briefing).mp4 9.8 MB
- 6. Multilinear Regression/19. Python - Model Predictions.mp4 9.8 MB
- 10. Matching/12. The Curse of Dimensionality.mp4 9.3 MB
- 3. Basic Statistics/2. Arithmetic Mean.mp4 9.1 MB
- 15. Random Forest/2. Ensemble Learning and Random Forest.mp4 9.0 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/2. Value Based Segmentation.mp4 9.0 MB
- 16. Facebook Prophet/8. Python - Renaming Variables.mp4 8.9 MB
- 10. Matching/1. Matching - Game Plan.mp4 8.9 MB
- 6. Multilinear Regression/6. Outliers.mp4 8.8 MB
- 4. Intermediary Statistics/22. Chi-square test.mp4 8.8 MB
- 13. Gaussian Mixture/10. Python - Gaussian Mixture Model.mp4 8.6 MB
- 16. Facebook Prophet/9. Dynamic Holidays.mp4 8.5 MB
- 4. Intermediary Statistics/14. Z-Score.mp4 8.4 MB
- 10. Matching/3. CASE STUDY Catholic Schools & Standardized Tests (Briefing).mp4 8.4 MB
- 3. Basic Statistics/7. Median and Mode.mp4 8.4 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/10. Python - Monetary Variable.mp4 8.3 MB
- 16. Facebook Prophet/12. Python - Finishing Holiday Preparation.mp4 8.3 MB
- 16. Facebook Prophet/26. Parameters to Tune.mp4 8.3 MB
- 16. Facebook Prophet/2. Structural Time Series.mp4 8.2 MB
- 4. Intermediary Statistics/11. Standard Error of the Mean.mp4 8.2 MB
- 15. Random Forest/13. Python - Predictions.mp4 7.9 MB
- 10. Matching/25. My Experience with Matching.mp4 7.8 MB
- 15. Random Forest/16. Parameter Tuning.mp4 7.6 MB
- 1. Introduction/2. Introduction.mp4 7.3 MB
- 3. Basic Statistics/15. Standard Deviation.mp4 7.3 MB
- 6. Multilinear Regression/13. Python - Adding Constant.mp4 7.0 MB
- 15. Random Forest/9. Random Forest Quirks.mp4 6.7 MB
- 10. Matching/20. Matching Robustness Check.mp4 6.6 MB
- 4. Intermediary Statistics/18. T-test.mp4 6.6 MB
- 3. Basic Statistics/17. EXERCISE Python - Standard Deviation.mp4 6.5 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/3. Time Series Data.mp4 6.4 MB
- 13. Gaussian Mixture/2. Clustering.mp4 6.2 MB
- 4. Intermediary Statistics/8. Shapiro-Wilks Test.mp4 6.1 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/6. Causal Impact Step-by-Step Guide.mp4 6.0 MB
- 16. Facebook Prophet/13. Training and Test Set in Time Series.mp4 5.8 MB
- 6. Multilinear Regression/2. The Concept of Multilinear Regression.mp4 5.3 MB
- 6. Multilinear Regression/14. Under and Over Fitting.mp4 5.1 MB
- 16. Facebook Prophet/1. Facebook Prophet - Game Plan.mp4 5.0 MB
- 6. Multilinear Regression/1. Multilinear Regression - Game Plan.mp4 4.2 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/2. Google Causal Impact - Game Plan.mp4 4.0 MB
- 16. Facebook Prophet/23. Cross-Validation.mp4 3.6 MB
- 5. Linear Regression/1. Linear Regression - Game Plan.mp4 3.6 MB
- 16. Facebook Prophet/4. CASE STUDY Wikipedia (Briefing).mp4 3.5 MB
- 5. Linear Regression/2. CASE STUDY Diamonds (Briefing).mp4 3.3 MB
- 15. Random Forest/1. Random Forest - Game Plan.mp4 3.3 MB
- 7. Logistic Regression/1. Logistic Regression - Game Plan.mp4 3.1 MB
- 6. Multilinear Regression/3. CASE STUDY Professors' Salary (Briefing).mp4 3.1 MB
- 13. Gaussian Mixture/4. CASE STUDY Credit Cards #1 (Briefing).mp4 3.0 MB
- 7. Logistic Regression/2. CASE STUDY Spam Emails (Briefing).mp4 3.0 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/4. CASE STUDY Online Shopping (Briefing).mp4 2.9 MB
- 3. Basic Statistics/1. Basic Statistics - Game Plan.mp4 2.9 MB
- 6. Multilinear Regression/15. Training and Test Set.mp4 2.8 MB
- 13. Gaussian Mixture/1. Gaussian Mixture - Game Plan.mp4 2.7 MB
- 4. Intermediary Statistics/19. CASE STUDY Remote Work Predictions (Briefing).mp4 2.4 MB
- 12. RFM (Recency, Frequency, Monetary) Analysis/1. RFM - Game Plan.mp4 2.3 MB
- 15. Random Forest/4. CASE STUDY Credit Cards #2 (Briefing).mp4 2.2 MB
- 3. Basic Statistics/3. CASE STUDY Moneyball (Briefing).mp4 2.2 MB
- 4. Intermediary Statistics/1. Intermediary Statistics - Game Plan.mp4 1.8 MB
- 9. Google Causal Impact (Econometrics and Causal Inference)/22. CHALLENGE Solutions.srt 21.7 KB
- 13. Gaussian Mixture/14. CHALLENGE Solutions.srt 19.7 KB
- 6. Multilinear Regression/22. CHALLENGE Solutions.srt 19.5 KB
- 16. Facebook Prophet/33. CHALLENGE Solutions (Part 3).srt 16.9 KB
- 16. Facebook Prophet/32. CHALLENGE Solutions (Part 2).srt 16.3 KB
- 10. Matching/24. CHALLENGE Solutions.srt 16.0 KB
- 7. Logistic Regression/20. CHALLENGE Solutions.srt 15.2 KB
- 12. RFM (Recency, Frequency, Monetary) Analysis/18. CHALLENGE Solutions.srt 12.8 KB
- 4. Intermediary Statistics/20. Python - T-test.srt 12.1 KB
- 16. Facebook Prophet/31. CHALLENGE Solutions (Part 1).srt 11.8 KB
- 3. Basic Statistics/13. Python - Correlation.srt 10.4 KB
- 3. Basic Statistics/5. Python - Mean.srt 10.3 KB
- 15. Random Forest/21. CHALLENGE Solutions (Part 2).srt 10.3 KB
- 9. Google Causal Impact (Econometrics and Causal Inference)/16. Python - Correlation Matrix and Heatmap.srt 10.2 KB
- 7. Logistic Regression/13. Python - Function to Read Coefficients.srt 10.0 KB
- 1. Introduction/5. Setting up the Course Material.srt 9.7 KB
- 10. Matching/13. Python - Transforming Race Variable.srt 9.6 KB
- 3. Basic Statistics/4. Python - Directory, Libraries and Data.srt 9.5 KB
- 15. Random Forest/20. CHALLENGE Solutions (Part 1).srt 9.2 KB
- 10. Matching/21. Python - Matching Robustness Repeated Samples.srt 9.1 KB
- 4. Intermediary Statistics/5. Python - Normal Distribution Visualization.srt 9.1 KB
- 13. Gaussian Mixture/12. Python - Interpretation.srt 9.0 KB
- 4. Intermediary Statistics/9. Python - Shapiro-Wilks Test.srt 8.9 KB
- 4. Intermediary Statistics/23. Python - Chi-square test.srt 8.7 KB
- 9. Google Causal Impact (Econometrics and Causal Inference)/15. Python - Stationarity.srt 8.7 KB
- 16. Facebook Prophet/20. Python - Event Assessment.srt 8.2 KB
- 16. Facebook Prophet/28. Python - Parameter Tuning.srt 8.2 KB
- 16. Facebook Prophet/19. Python - Forecasting.srt 7.9 KB
- 16. Facebook Prophet/22. Python - Visualization.srt 7.9 KB
- 7. Logistic Regression/6. Python - Histogram and Outlier Removal.srt 7.9 KB
- 10. Matching/19. Python - Matching Model.srt 7.7 KB
- 4. Intermediary Statistics/16. Python - Confidence Interval.srt 7.7 KB
- 15. Random Forest/18. Python - Parameter Tuning.srt 7.6 KB
- 7. Logistic Regression/17. Python - Manual Accuracy Assessment.srt 7.4 KB
- 7. Logistic Regression/15. Confusion Matrix.srt 7.3 KB
- 16. Facebook Prophet/25. Python - Cross-Validation Results and Visualization.srt 7.2 KB
- 16. Facebook Prophet/24. Python - Cross-Validation.srt 7.2 KB
- 12. RFM (Recency, Frequency, Monetary) Analysis/12. Python - Quartiles.srt 7.1 KB
- 16. Facebook Prophet/17. Python - Facebook Prophet.srt 7.0 KB
- 4. Intermediary Statistics/6. EXERCISE Python - Normal Distribution.srt 6.9 KB
- 4. Intermediary Statistics/7. P-value.srt 6.6 KB
- 13. Gaussian Mixture/9. Python - Optimal Number of Clusters.srt 6.6 KB
- 6. Multilinear Regression/20. Python - Accuracy Assessment.srt 6.6 KB
- 5. Linear Regression/12. EXERCISE Python - Linear Regression.srt 6.3 KB
- 1. Introduction/7. ZTM Resources.srt 6.3 KB
- 10. Matching/23. CHALLENGE Introduction.srt 6.3 KB
- 9. Google Causal Impact (Econometrics and Causal Inference)/21. CHALLENGE Introduction.srt 6.3 KB
- 4. Intermediary Statistics/15. Confidence interval.srt 6.3 KB
- 16. Facebook Prophet/11. Python - Black Friday Holiday.srt 6.2 KB
- 9. Google Causal Impact (Econometrics and Causal Inference)/20. Python - Causal Impact Results.srt 6.1 KB
- 12. RFM (Recency, Frequency, Monetary) Analysis/3. RFM Model.srt 6.1 KB
- 16. Facebook Prophet/6. Python - Loading and Inspecting the Data.srt 6.0 KB
- 16. Facebook Prophet/10. Python - Easter Holiday.srt 6.0 KB
- 4. Intermediary Statistics/21. EXERCISE Python - T-test.srt 6.0 KB
- 1. Introduction/3. Join Our Online Classroom!.srt 6.0 KB
- 10. Matching/9. Python - T-Test Loop.srt 5.9 KB
- 6. Multilinear Regression/4. Python - Preparing Script and Loading Data.srt 5.9 KB
- 4. Intermediary Statistics/4. Python - Preparing Script and Loading Data.srt 5.9 KB
- 5. Linear Regression/4. Python - Preparing Script and Loading Data.srt 5.6 KB
- 16. Facebook Prophet/27. Python - Parameter Grid.srt 5.6 KB
- 5. Linear Regression/3. Linear Regression.srt 5.5 KB
- 1. Introduction/6. The Modern Day Business Analyst.srt 5.5 KB
- 9. Google Causal Impact (Econometrics and Causal Inference)/12. Python - Data Preparation.srt 5.5 KB
- 10. Matching/18. Python - Plotting Common Support Region.srt 5.5 KB
- 7. Logistic Regression/16. Python - Confusion Matrix.srt 5.5 KB
- 10. Matching/14. Python - Transforming Education Variable.srt 5.4 KB
- 6. Multilinear Regression/7. Python - Plotting Continuous Variables.srt 5.4 KB
- 3. Basic Statistics/12. Correlation.srt 5.4 KB
- 16. Facebook Prophet/21. Python - Accuracy Assessment.srt 5.4 KB
- 16. Facebook Prophet/34. Forecasting at Uber.srt 5.4 KB
- 6. Multilinear Regression/21. CHALLENGE Introduction.srt 5.3 KB
- 6. Multilinear Regression/17. Python - Multilinear Regression.srt 5.3 KB
- 3. Basic Statistics/8. Python - Median.srt 5.1 KB
- 13. Gaussian Mixture/13. CHALLENGE Introduction.srt 5.1 KB
- 12. RFM (Recency, Frequency, Monetary) Analysis/16. Python - Results Summary.srt 5.0 KB
- 9. Google Causal Impact (Econometrics and Causal Inference)/9. Python - Load Bitcoin Price Data.srt 5.0 KB
- 10. Matching/17. Python - Logistic Regression for Common Support Region.srt 5.0 KB
- 6. Multilinear Regression/10. Python - For Loop.srt 4.9 KB
- 15. Random Forest/15. Python - Feature Importance.srt 4.9 KB
- 6. Multilinear Regression/9. Python - Categorical Variables.srt 4.9 KB
- 7. Logistic Regression/19. CHALLENGE Introduction.srt 4.9 KB
- 10. Matching/8. Python - T-Test.srt 4.8 KB
- 9. Google Causal Impact (Econometrics and Causal Inference)/8. Python - Dates.srt 4.8 KB
- 10. Matching/16. Common Support Region.srt 4.8 KB
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