[GigaCourse.Com] Udemy - Business Data Analytics & Intelligence with Python 2023

Creation Time	Nov. 4, 2024, 2:01 p.m.
Last Access Time	Nov. 25, 2024, 9:03 p.m.
File Size	5.7 GB
Keywords	Python Business with Com 2023 - Udemy Analytics GigaCourse Intelligence Data
Total Requests	8
Total Files	505
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13. Gaussian Mixture/14. CHALLENGE Solutions.mp4 160.6 MB
6. Multilinear Regression/22. CHALLENGE Solutions.mp4 110.6 MB
10. Matching/27. CHALLENGE Solutions.mp4 107.5 MB
9. Google Causal Impact (Econometrics and Causal Inference)/22. CHALLENGE Solutions.mp4 103.5 MB
7. Logistic Regression/20. CHALLENGE Solutions.mp4 90.6 MB
13. Gaussian Mixture/12. Python - Interpretation.mp4 78.7 MB
16. Facebook Prophet/30. CHALLENGE Solutions (Part 2).mp4 77.8 MB
1. Introduction/3. Join Our Online Classroom!.mp4 75.3 MB
10. Matching/18. Python - Logistic Regression and Debugging.mp4 73.9 MB
12. RFM (Recency, Frequency, Monetary) Analysis/18. CHALLENGE Solutions.mp4 72.7 MB
10. Matching/14. Python - Race Variable Transformation.mp4 66.8 MB
4. Intermediary Statistics/20. Python - T-test.mp4 65.5 MB
16. Facebook Prophet/24. Python - Cross-validation.mp4 59.9 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
7. Logistic Regression/13. Python - Function to Read Coefficients.mp4 56.7 MB
16. Facebook Prophet/27. Python - Parameter Tuning.mp4 56.5 MB
15. Random Forest/20. CHALLENGE Solutions (Part 1).mp4 55.9 MB
3. Basic Statistics/13. Python - Correlation.mp4 54.0 MB
9. Google Causal Impact (Econometrics and Causal Inference)/12. Python - Preparing DataFrame.mp4 54.0 MB
9. Google Causal Impact (Econometrics and Causal Inference)/15. Python - Stationarity.mp4 53.8 MB
10. Matching/23. Python - Robustness Check - Repeated experiments.mp4 53.7 MB
1. Introduction/1. Python for Business Analytics & Intelligence.mp4 53.6 MB
16. Facebook Prophet/29. CHALLENGE Solutions (Part 1).mp4 52.2 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
16. Facebook Prophet/31. CHALLENGE Solutions (Part 3).mp4 49.0 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
4. Intermediary Statistics/16. Python - Confidence Interval.mp4 45.8 MB
9. Google Causal Impact (Econometrics and Causal Inference)/20. Python - Impact Results.mp4 44.5 MB
4. Intermediary Statistics/15. Confidence interval.mp4 43.0 MB
6. Multilinear Regression/17. Python - Multilinear Regression.mp4 42.8 MB
12. RFM (Recency, Frequency, Monetary) Analysis/12. Python - Quartiles.mp4 41.8 MB
4. Intermediary Statistics/5. Python - Normal Distribution Visualization.mp4 40.9 MB
10. Matching/15. Python - Education Variables.mp4 40.8 MB
9. Google Causal Impact (Econometrics and Causal Inference)/21. CHALLENGE Introduction.mp4 40.1 MB
9. Google Causal Impact (Econometrics and Causal Inference)/18. Python - Google Causal Impact.mp4 39.9 MB
16. Facebook Prophet/17. Facebook Prophet Model.mp4 39.6 MB
6. Multilinear Regression/7. Python - Plotting Continuous Variables.mp4 39.4 MB
16. Facebook Prophet/22. Python - Visualization.mp4 39.2 MB
9. Google Causal Impact (Econometrics and Causal Inference)/23. EXERCISE Imposter Syndrome.mp4 39.2 MB
10. Matching/21. Python - Matching.mp4 39.1 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
6. Multilinear Regression/20. Python - Accuracy Assessment.mp4 37.5 MB
5. Linear Regression/12. EXERCISE Python - Linear Regression.mp4 36.0 MB
10. Matching/19. Python - Preparing for Common Support Region.mp4 36.0 MB
16. Facebook Prophet/19. Python - Future Dataframe.mp4 34.6 MB
10. Matching/26. CHALLENGE Introduction.mp4 34.3 MB
9. Google Causal Impact (Econometrics and Causal Inference)/9. Python - Bitcoin Price loading.mp4 33.6 MB
5. Linear Regression/7. Linear Regression Output.mp4 33.4 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
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
10. Matching/10. Python - Chi-square Test.mp4 31.1 MB
12. RFM (Recency, Frequency, Monetary) Analysis/9. Python - Customer Level Aggregation.mp4 30.4 MB
10. Matching/9. Python - T-Test Loop.mp4 30.3 MB
9. Google Causal Impact (Econometrics and Causal Inference)/16. Python - Correlation.mp4 30.2 MB
7. Logistic Regression/16. Python - Confusion Matrix.mp4 29.6 MB
3. Basic Statistics/12. Correlation.mp4 29.4 MB
10. Matching/11. Python - Chi-square Loop.mp4 29.4 MB
7. Logistic Regression/19. CHALLENGE Introduction.mp4 29.3 MB
15. Random Forest/19. CHALLENGE Introduction.mp4 29.1 MB
9. Google Causal Impact (Econometrics and Causal Inference)/11. Python - Load Control Groups.mp4 29.0 MB
4. Intermediary Statistics/12. Python - Standard Error.mp4 28.8 MB
10. Matching/25. Python - Robustness Check - Removing 1 Confounder.mp4 28.6 MB
4. Intermediary Statistics/4. Python - Preparing Script and Loading Data.mp4 28.6 MB
16. Facebook Prophet/10. Python - Easter Holidays.mp4 28.5 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
10. Matching/8. Python - T-Test.mp4 27.3 MB
4. Intermediary Statistics/7. P-value.mp4 27.3 MB
10. Matching/16. Python - Cleaning and Preparing Dataset.mp4 26.5 MB
6. Multilinear Regression/9. Python - Categorical Variables.mp4 26.5 MB
9. Google Causal Impact (Econometrics and Causal Inference)/19. Interpretation of Results.mp4 26.5 MB
5. Linear Regression/9. Python - Plotting Regression.mp4 26.1 MB
15. Random Forest/15. Python - Feature Importance.mp4 26.1 MB
10. Matching/5. Python - Loading Data.mp4 25.9 MB
16. Facebook Prophet/26. Python - Parameter Grid.mp4 25.5 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
16. Facebook Prophet/28. CHALLENGE Introduction.mp4 24.5 MB
10. Matching/17. Common Support Region.mp4 24.2 MB
3. Basic Statistics/14. EXERCISE Python - Correlation.mp4 24.2 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
4. Intermediary Statistics/24. EXERCISE Python - Chi-square.mp4 22.7 MB
16. Facebook Prophet/21. Python - Accuracy Assessment.mp4 22.6 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 21.9 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
16. Facebook Prophet/7. Python - Transforming Date Variable.mp4 20.7 MB
3. Basic Statistics/9. EXERCISE Python - Median.mp4 20.3 MB
10. Matching/7. Python - Comparing Means.mp4 20.0 MB
9. Google Causal Impact (Econometrics and Causal Inference)/13. Python - Preparing for Correlation Matrix.mp4 19.7 MB
15. Random Forest/6. Python - Loading Data.mp4 19.7 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
9. Google Causal Impact (Econometrics and Causal Inference)/7. Python - Installing and Importing Libraries.mp4 18.8 MB
12. RFM (Recency, Frequency, Monetary) Analysis/11. Python - Tidying up Dataframe.mp4 18.7 MB
16. Facebook Prophet/20. Python - Forecasting.mp4 18.6 MB
7. Logistic Regression/12. Python - Logistic Regression.mp4 18.6 MB
16. Facebook Prophet/11. Python - Black Friday.mp4 18.5 MB
9. Google Causal Impact (Econometrics and Causal Inference)/8. Python - Defining Dates.mp4 18.4 MB
9. Google Causal Impact (Econometrics and Causal Inference)/1. Why Econometrics and Causal Inference.mp4 18.3 MB
10. Matching/4. Python - Directory and Libraries.mp4 18.1 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
7. Logistic Regression/8. Python - Transforming Dependent Variable.mp4 17.3 MB
15. Random Forest/3. How Decision Trees Work.mp4 17.3 MB
16. Facebook Prophet/12. Python - Combining Events and Preparing Dataframe.mp4 17.0 MB
17. Where To Go From Here/1. Thank You!.mp4 16.9 MB
13. Gaussian Mixture/6. Python - Load Data.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
9. Google Causal Impact (Econometrics and Causal Inference)/14. Correlation Recap and Stationarity.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
9. Google Causal Impact (Econometrics and Causal Inference)/17. Python - Google Causal Impact Setup.mp4 16.0 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/32. Forecasting at Uber.mp4 15.6 MB
10. Matching/12. Python - Other Variables.mp4 15.5 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
16. Facebook Prophet/6. Python - Loading Data.mp4 14.4 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
16. Facebook Prophet/5. Python - Directory and Libraries.mp4 14.3 MB
12. RFM (Recency, Frequency, Monetary) Analysis/5. Python - Directory and Libraries.mp4 14.3 MB
9. Google Causal Impact (Econometrics and Causal Inference)/4. CASE STUDY Bitcoin Pricing (Briefing).mp4 14.2 MB
10. Matching/2. Matching.mp4 14.1 MB
15. Random Forest/5. Python - Directory and Libraries.mp4 13.9 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
16. Facebook Prophet/14. Python - Training and Test Set.mp4 12.7 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
9. Google Causal Impact (Econometrics and Causal Inference)/10. Assumptions.mp4 12.4 MB
5. Linear Regression/10. Dummy Variable Trap.mp4 12.1 MB
13. Gaussian Mixture/7. Python - Transform Character variables.mp4 12.1 MB
12. RFM (Recency, Frequency, Monetary) Analysis/13. Python - RFM Score.mp4 12.0 MB
16. Facebook Prophet/3. Facebook Prophet.mp4 11.8 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
10. Matching/24. Python - Outcome Visualization.mp4 11.4 MB
5. Linear Regression/5. Python - Isolate X and Y.mp4 11.0 MB
10. Matching/20. Python - Common Support Region Visualization.mp4 10.9 MB
7. Logistic Regression/11. How to Read Logistic Regression Coefficients.mp4 10.9 MB
16. Facebook Prophet/18. Python - Regressor Coefficients.mp4 10.5 MB
16. Facebook Prophet/8. Python - Renaming Variables.mp4 10.2 MB
13. Gaussian Mixture/8. AIC and BIC.mp4 10.1 MB
7. Logistic Regression/3. Logistic Regression.mp4 10.1 MB
16. Facebook Prophet/16. Additive vs. Multiplicative Seasonality.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
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
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
10. Matching/6. Unconfoundedness.mp4 8.5 MB
4. Intermediary Statistics/14. Z-Score.mp4 8.4 MB
3. Basic Statistics/7. Median and Mode.mp4 8.4 MB
9. Google Causal Impact (Econometrics and Causal Inference)/5. Difference-in-Differences Framework.mp4 8.4 MB
12. RFM (Recency, Frequency, Monetary) Analysis/10. Python - Monetary Variable.mp4 8.4 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
10. Matching/1. Matching - Game Plan.mp4 8.1 MB
16. Facebook Prophet/15. Facebook Prophet Parameters.mp4 8.1 MB
15. Random Forest/13. Python - Predictions.mp4 7.9 MB
10. Matching/28. My Experience with Matching.mp4 7.8 MB
15. Random Forest/16. Parameter Tuning.mp4 7.6 MB
10. Matching/13. The Curse of Dimensionality.mp4 7.5 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/22. Robustness Checks.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
16. Facebook Prophet/9. Dynamic Holidays.mp4 6.4 MB
16. Facebook Prophet/13. Training and Test Set.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.mp4 5.8 MB
9. Google Causal Impact (Econometrics and Causal Inference)/3. Time Series Data.mp4 5.7 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
10. Matching/3. CASE STUDY Catholic Schools & Standardized Tests (Briefing).mp4 4.7 MB
6. Multilinear Regression/1. Multilinear Regression - Game Plan.mp4 4.2 MB
16. Facebook Prophet/25. Parameters to tune.mp4 3.8 MB
9. Google Causal Impact (Econometrics and Causal Inference)/2. Google Causal Impact - Game Plan.mp4 3.6 MB
5. Linear Regression/1. Linear Regression - Game Plan.mp4 3.6 MB
16. Facebook Prophet/1. Facebook Prophet - Game Plan.mp4 3.4 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
16. Facebook Prophet/23. Cross-validation.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
16. Facebook Prophet/4. CASE STUDY Wikipedia (Briefing).mp4 2.6 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
13. Gaussian Mixture/14. CHALLENGE Solutions.srt 19.7 KB
6. Multilinear Regression/22. CHALLENGE Solutions.srt 19.5 KB
10. Matching/27. CHALLENGE Solutions.srt 16.0 KB
7. Logistic Regression/20. CHALLENGE Solutions.srt 15.2 KB
9. Google Causal Impact (Econometrics and Causal Inference)/22. CHALLENGE Solutions.srt 13.6 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/30. CHALLENGE Solutions (Part 2).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
7. Logistic Regression/13. Python - Function to Read Coefficients.srt 10.0 KB
16. Facebook Prophet/29. CHALLENGE Solutions (Part 1).srt 9.9 KB
1. Introduction/5. Setting up the Course Material.srt 9.7 KB
9. Google Causal Impact (Econometrics and Causal Inference)/15. Python - Stationarity.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
4. Intermediary Statistics/5. Python - Normal Distribution Visualization.srt 9.1 KB
13. Gaussian Mixture/12. Python - Interpretation.srt 9.0 KB
16. Facebook Prophet/24. Python - Cross-validation.srt 8.9 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
10. Matching/18. Python - Logistic Regression and Debugging.srt 8.4 KB
16. Facebook Prophet/31. CHALLENGE Solutions (Part 3).srt 8.2 KB
7. Logistic Regression/6. Python - Histogram and Outlier Removal.srt 7.9 KB
10. Matching/14. Python - Race Variable Transformation.srt 7.8 KB
4. Intermediary Statistics/16. Python - Confidence Interval.srt 7.7 KB
10. Matching/23. Python - Robustness Check - Repeated experiments.srt 7.7 KB
15. Random Forest/18. Python - Parameter Tuning.srt 7.6 KB
16. Facebook Prophet/27. Python - Parameter Tuning.srt 7.5 KB
7. Logistic Regression/17. Python - Manual Accuracy Assessment.srt 7.4 KB
7. Logistic Regression/15. Confusion Matrix.srt 7.3 KB
12. RFM (Recency, Frequency, Monetary) Analysis/12. Python - Quartiles.srt 7.1 KB
9. Google Causal Impact (Econometrics and Causal Inference)/21. CHALLENGE Introduction.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
16. Facebook Prophet/22. Python - Visualization.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
10. Matching/26. CHALLENGE Introduction.srt 6.3 KB
4. Intermediary Statistics/15. Confidence interval.srt 6.3 KB
9. Google Causal Impact (Econometrics and Causal Inference)/12. Python - Preparing DataFrame.srt 6.1 KB
12. RFM (Recency, Frequency, Monetary) Analysis/3. RFM Model.srt 6.1 KB
9. Google Causal Impact (Econometrics and Causal Inference)/9. Python - Bitcoin Price loading.srt 6.1 KB
4. Intermediary Statistics/21. EXERCISE Python - T-test.srt 6.0 KB
1. Introduction/3. Join Our Online Classroom!.srt 6.0 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
10. Matching/19. Python - Preparing for Common Support Region.srt 5.9 KB
10. Matching/15. Python - Education Variables.srt 5.8 KB
16. Facebook Prophet/10. Python - Easter Holidays.srt 5.8 KB
9. Google Causal Impact (Econometrics and Causal Inference)/20. Python - Impact Results.srt 5.8 KB
16. Facebook Prophet/28. CHALLENGE Introduction.srt 5.7 KB
5. Linear Regression/4. Python - Preparing Script and Loading Data.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
7. Logistic Regression/16. Python - Confusion Matrix.srt 5.5 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/32. Forecasting at Uber.srt 5.4 KB
6. Multilinear Regression/21. CHALLENGE Introduction.srt 5.3 KB
10. Matching/9. Python - T-Test Loop.srt 5.3 KB
6. Multilinear Regression/17. Python - Multilinear Regression.srt 5.3 KB
10. Matching/21. Python - Matching.srt 5.3 KB
16. Facebook Prophet/17. Facebook Prophet Model.srt 5.2 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
6. Multilinear Regression/10. Python - For Loop.srt 4.9 KB
10. Matching/11. Python - Chi-square 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
16. Facebook Prophet/19. Python - Future Dataframe.srt 4.9 KB
7. Logistic Regression/4. Python - Preparing Script and Loading Data.srt 4.7 KB
12. RFM (Recency, Frequency, Monetary) Analysis/14. Python - RFM Function.srt 4.7 KB
15. Random Forest/19. CHALLENGE Introduction.srt 4.7 KB
4. Intermediary Statistics/12. Python - Standard Error.srt 4.6 KB
9. Google Causal Impact (Econometrics and Causal Inference)/14. Correlation Recap and Stationarity.srt 4.6 KB
15. Random Forest/3. How Decision Trees Work.srt 4.5 KB
10. Matching/8. Python - T-Test.srt 4.5 KB
5. Linear Regression/9. Python - Plotting Regression.srt 4.5 KB
9. Google Causal Impact (Econometrics and Causal Inference)/23. EXERCISE Imposter Syndrome.srt 4.5 KB
9. Google Causal Impact (Econometrics and Causal Inference)/1. Why Econometrics and Causal Inference.srt 4.5 KB
9. Google Causal Impact (Econometrics and Causal Inference)/19. Interpretation of Results.srt 4.4 KB
13. Gaussian Mixture/3. Gaussian Mixture Model.srt 4.3 KB
9. Google Causal Impact (Econometrics and Causal Inference)/7. Python - Installing and Importing Libraries.srt 4.3 KB
6. Multilinear Regression/12. Python - Isolate X and Y.srt 4.2 KB
16. Facebook Prophet/26. Python - Parameter Grid.srt 4.2 KB
3. Basic Statistics/18. CASE STUDY Moneyball.srt 4.2 KB
3. Basic Statistics/14. EXERCISE Python - Correlation.srt 4.2 KB
10. Matching/17. Common Support Region.srt 4.1 KB
10. Matching/10. Python - Chi-square Test.srt 4.1 KB
9. Google Causal Impact (Econometrics and Causal Inference)/11. Python - Load Control Groups.srt 4.1 KB
9. Google Causal Impact (Econometrics and Causal Inference)/8. Python - Defining Dates.srt 4.0 KB
16. Facebook Prophet/3. Facebook Prophet.srt 4.0 KB
5. Linear Regression/11. Python - Dummy Variable.srt 4.0 KB
12. RFM (Recency, Frequency, Monetary) Analysis/9. Python - Customer Level Aggregation.srt 4.0 KB
4. Intermediary Statistics/25. Powerposing and p-hacking.srt 4.0 KB
12. RFM (Recency, Frequency, Monetary) Analysis/17. CHALLENGE Introduction.srt 3.9 KB
10. Matching/25. Python - Robustness Check - Removing 1 Confounder.srt 3.8 KB
9. Google Causal Impact (Econometrics and Causal Inference)/18. Python - Google Causal Impact.srt 3.8 KB
12. RFM (Recency, Frequency, Monetary) Analysis/8. Python - Date Variable.srt 3.8 KB
5. Linear Regression/10. Dummy Variable Trap.srt 3.8 KB
13. Gaussian Mixture/15. My Experience with Segmentation.srt 3.8 KB
16. Facebook Prophet/21. Python - Accuracy Assessment.srt 3.8 KB
5. Linear Regression/7. Linear Regression Output.srt 3.8 KB
1. Introduction/4. Exercise Meet Your Classmates + Instructor.html 3.8 KB
3. Basic Statistics/9. EXERCISE Python - Median.srt 3.7 KB
15. Random Forest/14. Python - Classification Report and F1 score.srt 3.7 KB
4. Intermediary Statistics/24. EXERCISE Python - Chi-square.srt 3.7 KB
16. Facebook Prophet/14. Python - Training and Test Set.srt 3.6 KB
10. Matching/16. Python - Cleaning and Preparing Dataset.srt 3.6 KB
5. Linear Regression/8. Python - Linear Regression model and summary.srt 3.6 KB
7. Logistic Regression/14. Python - Predictions.srt 3.6 KB
15. Random Forest/17. Python - Parameter Grid.srt 3.5 KB
6. Multilinear Regression/11. Python - Creating Dummy Variables.srt 3.5 KB
1. Introduction/1. Python for Business Analytics & Intelligence.srt 3.5 KB
6. Multilinear Regression/18. Accuracy KPIs (Key Performance Indicators).srt 3.5 KB
4. Intermediary Statistics/2. Normal Distribution.srt 3.4 KB
15. Random Forest/11. Python - Training and Test Set.srt 3.4 KB
10. Matching/2. Matching.srt 3.4 KB
6. Multilinear Regression/5. Python - Summary Statistics.srt 3.4 KB
3. Basic Statistics/10. Python - Mode.srt 3.3 KB
16. Facebook Prophet/11. Python - Black Friday.srt 3.3 KB
12. RFM (Recency, Frequency, Monetary) Analysis/2. Value Based Segmentation.srt 3.3 KB
6. Multilinear Regression/8. Python - Correlation Matrix.srt 3.3 KB
9. Google Causal Impact (Econometrics and Causal Inference)/16. Python - Correlation.srt 3.3 KB
7. Logistic Regression/5. Python - Summary Statistics.srt 3.3 KB
6. Multilinear Regression/6. Outliers.srt 3.3 KB
3. Basic Statistics/7. Median and Mode.srt 3.3 KB
5. Linear Regression/6. Python - Adding Constant.srt 3.3 KB
10. Matching/1. Matching - Game Plan.srt 3.3 KB
4. Intermediary Statistics/10. EXERCISE Python - Shapiro-Wilks.srt 3.2 KB
15. Random Forest/12. Python - Random Forest Model.srt 3.2 KB
9. Google Causal Impact (Econometrics and Causal Inference)/10. Assumptions.srt 3.2 KB
10. Matching/28. My Experience with Matching.srt 3.1 KB
4. Intermediary Statistics/11. Standard Error of the Mean.srt 3.1 KB
4. Intermediary Statistics/3. CASE STUDY Wine Quality (Briefing).srt 3.1 KB
16. Facebook Prophet/7. Python - Transforming Date Variable.srt 3.1 KB
13. Gaussian Mixture/11. Python - Cluster Prediction and Assignment.srt 3.0 KB
10. Matching/4. Python - Directory and Libraries.srt 3.0 KB
4. Intermediary Statistics/13. EXERCISE Python - Standard Error.srt 3.0 KB
12. RFM (Recency, Frequency, Monetary) Analysis/6. Python - Loading Data.srt 3.0 KB
15. Random Forest/16. Parameter Tuning.srt 3.0 KB
4. Intermediary Statistics/14. Z-Score.srt 2.9 KB
12. RFM (Recency, Frequency, Monetary) Analysis/11. Python - Tidying up Dataframe.srt 2.9 KB
7. Logistic Regression/8. Python - Transforming Dependent Variable.srt 2.9 KB
7. Logistic Regression/10. Python - Training and Test Set.srt 2.9 KB
10. Matching/7. Python - Comparing Means.srt 2.9 KB
4. Intermediary Statistics/22. Chi-square test.srt 2.8 KB
7. Logistic Regression/18. Python - Classification Report.srt 2.8 KB
7. Logistic Regression/11. How to Read Logistic Regression Coefficients.srt 2.8 KB
16. Facebook Prophet/6. Python - Loading Data.srt 2.8 KB
9. Google Causal Impact (Econometrics and Causal Inference)/13. Python - Preparing for Correlation Matrix.srt 2.8 KB
16. Facebook Prophet/12. Python - Combining Events and Preparing Dataframe.srt 2.8 KB
10. Matching/5. Python - Loading Data.srt 2.8 KB
15. Random Forest/9. Random Forest Quirks.srt 2.8 KB
16. Facebook Prophet/2. Structural Time Series.srt 2.7 KB
16. Facebook Prophet/20. Python - Forecasting.srt 2.7 KB
9. Google Causal Impact (Econometrics and Causal Inference)/4. CASE STUDY Bitcoin Pricing (Briefing).srt 2.7 KB
16. Facebook Prophet/16. Additive vs. Multiplicative Seasonality.srt 2.7 KB
3. Basic Statistics/15. Standard Deviation.srt 2.7 KB
12. RFM (Recency, Frequency, Monetary) Analysis/15. Python - Applying RFM Function.srt 2.6 KB
3. Basic Statistics/16. Python - Standard Deviation.srt 2.6 KB
4. Intermediary Statistics/17. EXERCISE Python - Confidence Interval.srt 2.6 KB
3. Basic Statistics/2. Arithmetic Mean.srt 2.6 KB
6. Multilinear Regression/16. Python - Train and Test Split.srt 2.6 KB
9. Google Causal Impact (Econometrics and Causal Inference)/6. Causal Impact Step-by-Step.srt 2.6 KB
10. Matching/6. Unconfoundedness.srt 2.6 KB
10. Matching/22. Robustness Checks.srt 2.6 KB
7. Logistic Regression/12. Python - Logistic Regression.srt 2.6 KB
7. Logistic Regression/7. Python - Correlation Matrix.srt 2.6 KB
4. Intermediary Statistics/18. T-test.srt 2.5 KB
15. Random Forest/8. Python - Summary Statistics.srt 2.5 KB
7. Logistic Regression/9. Python - Prepare X and Y.srt 2.5 KB
15. Random Forest/2. Ensemble Learning and Random Forest.srt 2.5 KB
13. Gaussian Mixture/2. Clustering.srt 2.5 KB
15. Random Forest/5. Python - Directory and Libraries.srt 2.5 KB
16. Facebook Prophet/9. Dynamic Holidays.srt 2.5 KB
9. Google Causal Impact (Econometrics and Causal Inference)/17. Python - Google Causal Impact Setup.srt 2.4 KB
3. Basic Statistics/6. EXERCISE Python - Mean.srt 2.4 KB
16. Facebook Prophet/5. Python - Directory and Libraries.srt 2.4 KB
13. Gaussian Mixture/8. AIC and BIC.srt 2.4 KB
1. Introduction/2. Introduction.srt 2.4 KB
9. Google Causal Impact (Econometrics and Causal Inference)/5. Difference-in-Differences Framework.srt 2.4 KB
12. RFM (Recency, Frequency, Monetary) Analysis/5. Python - Directory and Libraries.srt 2.4 KB
16. Facebook Prophet/15. Facebook Prophet Parameters.srt 2.3 KB
16. Facebook Prophet/13. Training and Test Set.srt 2.3 KB
6. Multilinear Regression/2. The Concept of Multilinear Regression.srt 2.2 KB
7. Logistic Regression/3. Logistic Regression.srt 2.2 KB
13. Gaussian Mixture/5. Python - Directory and Data.srt 2.2 KB
4. Intermediary Statistics/8. Shapiro-Wilks Test.srt 2.1 KB
13. Gaussian Mixture/6. Python - Load Data.srt 2.1 KB
15. Random Forest/6. Python - Loading Data.srt 2.0 KB
11. PART C SEGMENTATION/1. What is Segmentation and why is it important.html 2.0 KB
5. Linear Regression/5. Python - Isolate X and Y.srt 2.0 KB
15. Random Forest/7. Python - Transform Object into Numerical Variables.srt 2.0 KB
12. RFM (Recency, Frequency, Monetary) Analysis/13. Python - RFM Score.srt 2.0 KB
12. RFM (Recency, Frequency, Monetary) Analysis/7. Python - Creating Sales Variable.srt 2.0 KB
3. Basic Statistics/11. EXERCISE Python - Mode.srt 1.9 KB
10. Matching/24. Python - Outcome Visualization.srt 1.9 KB
10. Matching/13. The Curse of Dimensionality.srt 1.8 KB
10. Matching/12. Python - Other Variables.srt 1.8 KB
17. Where To Go From Here/1. Thank You!.srt 1.8 KB
6. Multilinear Regression/1. Multilinear Regression - Game Plan.srt 1.8 KB
15. Random Forest/10. Python - Isolate X and Y.srt 1.8 KB
10. Matching/20. Python - Common Support Region Visualization.srt 1.8 KB
8. PART B ECONOMETRICS & CAUSAL INFERENCE/1. What are Econometrics & Causal Inference, and why are they important.html 1.7 KB
6. Multilinear Regression/19. Python - Model Predictions.srt 1.7 KB
16. Facebook Prophet/25. Parameters to tune.srt 1.7 KB
16. Facebook Prophet/8. Python - Renaming Variables.srt 1.7 KB
5. Linear Regression/1. Linear Regression - Game Plan.srt 1.7 KB
16. Facebook Prophet/18. Python - Regressor Coefficients.srt 1.7 KB
6. Multilinear Regression/14. Under and Over Fitting.srt 1.7 KB
9. Google Causal Impact (Econometrics and Causal Inference)/3. Time Series Data.srt 1.7 KB
14. PART D PREDICTIVE ANALYTICS/1. What are Predictive Analytics and why are they important.html 1.7 KB
6. Multilinear Regression/13. Python - Adding Constant.srt 1.6 KB
1. Introduction/7. Monthly Coding Challenges, Free Resources and Guides.html 1.6 KB
2. PART A STATISTICS/1. What are Statistics and why are they important.html 1.6 KB
16. Facebook Prophet/1. Facebook Prophet - Game Plan.srt 1.5 KB
15. Random Forest/13. Python - Predictions.srt 1.5 KB
9. Google Causal Impact (Econometrics and Causal Inference)/2. Google Causal Impact - Game Plan.srt 1.5 KB
13. Gaussian Mixture/1. Gaussian Mixture - Game Plan.srt 1.4 KB
7. Logistic Regression/1. Logistic Regression - Game Plan.srt 1.4 KB
17. Where To Go From Here/3. Endorsements On LinkedIn.html 1.4 KB
13. Gaussian Mixture/10. Python - Gaussian Mixture Model.srt 1.4 KB
12. RFM (Recency, Frequency, Monetary) Analysis/10. Python - Monetary Variable.srt 1.4 KB
13. Gaussian Mixture/7. Python - Transform Character variables.srt 1.4 KB
3. Basic Statistics/17. EXERCISE Python - Standard Deviation.srt 1.3 KB
3. Basic Statistics/1. Basic Statistics - Game Plan.srt 1.3 KB
3. Basic Statistics/3. CASE STUDY Moneyball (Briefing).srt 1.3 KB
18. BONUS Section/1. Special Bonus Lecture.html 1.2 KB
15. Random Forest/1. Random Forest - Game Plan.srt 1.2 KB
10. Matching/3. CASE STUDY Catholic Schools & Standardized Tests (Briefing).srt 1.2 KB
6. Multilinear Regression/15. Training and Test Set.srt 1.2 KB
16. Facebook Prophet/23. Cross-validation.srt 1.2 KB
5. Linear Regression/2. CASE STUDY Diamonds (Briefing).srt 1.1 KB
7. Logistic Regression/2. CASE STUDY Spam Emails (Briefing).srt 1.1 KB
12. RFM (Recency, Frequency, Monetary) Analysis/4. CASE STUDY Online Shopping (Briefing).srt 1.1 KB
13. Gaussian Mixture/4. CASE STUDY Credit Cards #1 (Briefing).srt 1.1 KB
6. Multilinear Regression/3. CASE STUDY Professors' Salary (Briefing).srt 1019 bytes
16. Facebook Prophet/4. CASE STUDY Wikipedia (Briefing).srt 975 bytes
4. Intermediary Statistics/1. Intermediary Statistics - Game Plan.srt 971 bytes
17. Where To Go From Here/2. Become An Alumni.html 921 bytes
4. Intermediary Statistics/19. CASE STUDY Remote Work Predictions (Briefing).srt 875 bytes
15. Random Forest/4. CASE STUDY Credit Cards #2 (Briefing).srt 860 bytes
17. Where To Go From Here/5. Coding Challenges.html 860 bytes
12. RFM (Recency, Frequency, Monetary) Analysis/1. RFM - Game Plan.srt 849 bytes
17. Where To Go From Here/4. Learning Guideline.html 353 bytes
0. Websites you may like/[CourseClub.Me].url 122 bytes
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12. RFM (Recency, Frequency, Monetary) Analysis/[CourseClub.Me].url 122 bytes
16. Facebook Prophet/[CourseClub.Me].url 122 bytes
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1. Introduction/5.1 Course Materials.html 99 bytes
1. Introduction/5.2 Sign up for your free Google Drive account here..html 85 bytes
0. Websites you may like/[GigaCourse.Com].url 49 bytes
1. Introduction/[GigaCourse.Com].url 49 bytes
12. RFM (Recency, Frequency, Monetary) Analysis/[GigaCourse.Com].url 49 bytes
16. Facebook Prophet/[GigaCourse.Com].url 49 bytes
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