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

  • 收录时间:2023-08-30 22:29:21
  • 文件大小:6GB
  • 下载次数:1
  • 最近下载:2023-08-30 22:29:21
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文件列表

  1. 13. Gaussian Mixture/14. CHALLENGE Solutions.mp4 161MB
  2. 6. Multilinear Regression/22. CHALLENGE Solutions.mp4 111MB
  3. 10. Matching/27. CHALLENGE Solutions.mp4 108MB
  4. 9. Google Causal Impact (Econometrics and Causal Inference)/22. CHALLENGE Solutions.mp4 104MB
  5. 7. Logistic Regression/20. CHALLENGE Solutions.mp4 91MB
  6. 13. Gaussian Mixture/12. Python - Interpretation.mp4 79MB
  7. 16. Facebook Prophet/30. CHALLENGE Solutions (Part 2).mp4 78MB
  8. 1. Introduction/3. Join Our Online Classroom!.mp4 75MB
  9. 10. Matching/18. Python - Logistic Regression and Debugging.mp4 74MB
  10. 12. RFM (Recency, Frequency, Monetary) Analysis/18. CHALLENGE Solutions.mp4 73MB
  11. 10. Matching/14. Python - Race Variable Transformation.mp4 67MB
  12. 4. Intermediary Statistics/20. Python - T-test.mp4 65MB
  13. 16. Facebook Prophet/24. Python - Cross-validation.mp4 60MB
  14. 3. Basic Statistics/5. Python - Mean.mp4 60MB
  15. 15. Random Forest/21. CHALLENGE Solutions (Part 2).mp4 59MB
  16. 1. Introduction/5. Setting up the Course Material.mp4 58MB
  17. 7. Logistic Regression/13. Python - Function to Read Coefficients.mp4 57MB
  18. 16. Facebook Prophet/27. Python - Parameter Tuning.mp4 56MB
  19. 15. Random Forest/20. CHALLENGE Solutions (Part 1).mp4 56MB
  20. 3. Basic Statistics/13. Python - Correlation.mp4 54MB
  21. 9. Google Causal Impact (Econometrics and Causal Inference)/12. Python - Preparing DataFrame.mp4 54MB
  22. 9. Google Causal Impact (Econometrics and Causal Inference)/15. Python - Stationarity.mp4 54MB
  23. 10. Matching/23. Python - Robustness Check - Repeated experiments.mp4 54MB
  24. 1. Introduction/1. Python for Business Analytics & Intelligence.mp4 54MB
  25. 16. Facebook Prophet/29. CHALLENGE Solutions (Part 1).mp4 52MB
  26. 3. Basic Statistics/4. Python - Directory, Libraries and Data.mp4 51MB
  27. 4. Intermediary Statistics/9. Python - Shapiro-Wilks Test.mp4 51MB
  28. 4. Intermediary Statistics/23. Python - Chi-square test.mp4 50MB
  29. 16. Facebook Prophet/31. CHALLENGE Solutions (Part 3).mp4 49MB
  30. 7. Logistic Regression/6. Python - Histogram and Outlier Removal.mp4 48MB
  31. 15. Random Forest/18. Python - Parameter Tuning.mp4 48MB
  32. 4. Intermediary Statistics/16. Python - Confidence Interval.mp4 46MB
  33. 9. Google Causal Impact (Econometrics and Causal Inference)/20. Python - Impact Results.mp4 45MB
  34. 4. Intermediary Statistics/15. Confidence interval.mp4 43MB
  35. 6. Multilinear Regression/17. Python - Multilinear Regression.mp4 43MB
  36. 12. RFM (Recency, Frequency, Monetary) Analysis/12. Python - Quartiles.mp4 42MB
  37. 4. Intermediary Statistics/5. Python - Normal Distribution Visualization.mp4 41MB
  38. 10. Matching/15. Python - Education Variables.mp4 41MB
  39. 9. Google Causal Impact (Econometrics and Causal Inference)/21. CHALLENGE Introduction.mp4 40MB
  40. 9. Google Causal Impact (Econometrics and Causal Inference)/18. Python - Google Causal Impact.mp4 40MB
  41. 16. Facebook Prophet/17. Facebook Prophet Model.mp4 40MB
  42. 6. Multilinear Regression/7. Python - Plotting Continuous Variables.mp4 39MB
  43. 16. Facebook Prophet/22. Python - Visualization.mp4 39MB
  44. 9. Google Causal Impact (Econometrics and Causal Inference)/23. EXERCISE Imposter Syndrome.mp4 39MB
  45. 10. Matching/21. Python - Matching.mp4 39MB
  46. 13. Gaussian Mixture/9. Python - Optimal Number of Clusters.mp4 39MB
  47. 7. Logistic Regression/17. Python - Manual Accuracy Assessment.mp4 38MB
  48. 6. Multilinear Regression/20. Python - Accuracy Assessment.mp4 38MB
  49. 5. Linear Regression/12. EXERCISE Python - Linear Regression.mp4 36MB
  50. 10. Matching/19. Python - Preparing for Common Support Region.mp4 36MB
  51. 16. Facebook Prophet/19. Python - Future Dataframe.mp4 35MB
  52. 10. Matching/26. CHALLENGE Introduction.mp4 34MB
  53. 9. Google Causal Impact (Econometrics and Causal Inference)/9. Python - Bitcoin Price loading.mp4 34MB
  54. 5. Linear Regression/7. Linear Regression Output.mp4 33MB
  55. 13. Gaussian Mixture/13. CHALLENGE Introduction.mp4 33MB
  56. 6. Multilinear Regression/4. Python - Preparing Script and Loading Data.mp4 33MB
  57. 4. Intermediary Statistics/21. EXERCISE Python - T-test.mp4 32MB
  58. 15. Random Forest/11. Python - Training and Test Set.mp4 32MB
  59. 10. Matching/10. Python - Chi-square Test.mp4 31MB
  60. 12. RFM (Recency, Frequency, Monetary) Analysis/9. Python - Customer Level Aggregation.mp4 30MB
  61. 10. Matching/9. Python - T-Test Loop.mp4 30MB
  62. 9. Google Causal Impact (Econometrics and Causal Inference)/16. Python - Correlation.mp4 30MB
  63. 7. Logistic Regression/16. Python - Confusion Matrix.mp4 30MB
  64. 3. Basic Statistics/12. Correlation.mp4 29MB
  65. 10. Matching/11. Python - Chi-square Loop.mp4 29MB
  66. 7. Logistic Regression/19. CHALLENGE Introduction.mp4 29MB
  67. 15. Random Forest/19. CHALLENGE Introduction.mp4 29MB
  68. 9. Google Causal Impact (Econometrics and Causal Inference)/11. Python - Load Control Groups.mp4 29MB
  69. 4. Intermediary Statistics/12. Python - Standard Error.mp4 29MB
  70. 10. Matching/25. Python - Robustness Check - Removing 1 Confounder.mp4 29MB
  71. 4. Intermediary Statistics/4. Python - Preparing Script and Loading Data.mp4 29MB
  72. 16. Facebook Prophet/10. Python - Easter Holidays.mp4 28MB
  73. 4. Intermediary Statistics/6. EXERCISE Python - Normal Distribution.mp4 28MB
  74. 6. Multilinear Regression/10. Python - For Loop.mp4 28MB
  75. 7. Logistic Regression/5. Python - Summary Statistics.mp4 28MB
  76. 7. Logistic Regression/4. Python - Preparing Script and Loading Data.mp4 28MB
  77. 6. Multilinear Regression/21. CHALLENGE Introduction.mp4 28MB
  78. 5. Linear Regression/4. Python - Preparing Script and Loading Data.mp4 27MB
  79. 12. RFM (Recency, Frequency, Monetary) Analysis/16. Python - Results Summary.mp4 27MB
  80. 10. Matching/8. Python - T-Test.mp4 27MB
  81. 4. Intermediary Statistics/7. P-value.mp4 27MB
  82. 10. Matching/16. Python - Cleaning and Preparing Dataset.mp4 27MB
  83. 6. Multilinear Regression/9. Python - Categorical Variables.mp4 27MB
  84. 9. Google Causal Impact (Econometrics and Causal Inference)/19. Interpretation of Results.mp4 26MB
  85. 5. Linear Regression/9. Python - Plotting Regression.mp4 26MB
  86. 15. Random Forest/15. Python - Feature Importance.mp4 26MB
  87. 10. Matching/5. Python - Loading Data.mp4 26MB
  88. 16. Facebook Prophet/26. Python - Parameter Grid.mp4 26MB
  89. 3. Basic Statistics/8. Python - Median.mp4 25MB
  90. 15. Random Forest/14. Python - Classification Report and F1 score.mp4 25MB
  91. 7. Logistic Regression/15. Confusion Matrix.mp4 25MB
  92. 16. Facebook Prophet/28. CHALLENGE Introduction.mp4 24MB
  93. 10. Matching/17. Common Support Region.mp4 24MB
  94. 3. Basic Statistics/14. EXERCISE Python - Correlation.mp4 24MB
  95. 15. Random Forest/8. Python - Summary Statistics.mp4 24MB
  96. 12. RFM (Recency, Frequency, Monetary) Analysis/6. Python - Loading Data.mp4 24MB
  97. 4. Intermediary Statistics/24. EXERCISE Python - Chi-square.mp4 23MB
  98. 16. Facebook Prophet/21. Python - Accuracy Assessment.mp4 23MB
  99. 12. RFM (Recency, Frequency, Monetary) Analysis/14. Python - RFM Function.mp4 22MB
  100. 5. Linear Regression/8. Python - Linear Regression model and summary.mp4 22MB
  101. 12. RFM (Recency, Frequency, Monetary) Analysis/8. Python - Date Variable.mp4 22MB
  102. 7. Logistic Regression/10. Python - Training and Test Set.mp4 22MB
  103. 7. Logistic Regression/14. Python - Predictions.mp4 21MB
  104. 6. Multilinear Regression/8. Python - Correlation Matrix.mp4 21MB
  105. 6. Multilinear Regression/12. Python - Isolate X and Y.mp4 21MB
  106. 16. Facebook Prophet/7. Python - Transforming Date Variable.mp4 21MB
  107. 3. Basic Statistics/9. EXERCISE Python - Median.mp4 20MB
  108. 10. Matching/7. Python - Comparing Means.mp4 20MB
  109. 9. Google Causal Impact (Econometrics and Causal Inference)/13. Python - Preparing for Correlation Matrix.mp4 20MB
  110. 15. Random Forest/6. Python - Loading Data.mp4 20MB
  111. 7. Logistic Regression/18. Python - Classification Report.mp4 20MB
  112. 1. Introduction/6. The Modern Day Business Analyst.mp4 20MB
  113. 3. Basic Statistics/10. Python - Mode.mp4 19MB
  114. 6. Multilinear Regression/5. Python - Summary Statistics.mp4 19MB
  115. 9. Google Causal Impact (Econometrics and Causal Inference)/7. Python - Installing and Importing Libraries.mp4 19MB
  116. 12. RFM (Recency, Frequency, Monetary) Analysis/11. Python - Tidying up Dataframe.mp4 19MB
  117. 16. Facebook Prophet/20. Python - Forecasting.mp4 19MB
  118. 7. Logistic Regression/12. Python - Logistic Regression.mp4 19MB
  119. 16. Facebook Prophet/11. Python - Black Friday.mp4 19MB
  120. 9. Google Causal Impact (Econometrics and Causal Inference)/8. Python - Defining Dates.mp4 18MB
  121. 9. Google Causal Impact (Econometrics and Causal Inference)/1. Why Econometrics and Causal Inference.mp4 18MB
  122. 10. Matching/4. Python - Directory and Libraries.mp4 18MB
  123. 12. RFM (Recency, Frequency, Monetary) Analysis/17. CHALLENGE Introduction.mp4 18MB
  124. 5. Linear Regression/11. Python - Dummy Variable.mp4 18MB
  125. 15. Random Forest/12. Python - Random Forest Model.mp4 18MB
  126. 15. Random Forest/17. Python - Parameter Grid.mp4 18MB
  127. 3. Basic Statistics/16. Python - Standard Deviation.mp4 18MB
  128. 6. Multilinear Regression/11. Python - Creating Dummy Variables.mp4 18MB
  129. 7. Logistic Regression/8. Python - Transforming Dependent Variable.mp4 17MB
  130. 15. Random Forest/3. How Decision Trees Work.mp4 17MB
  131. 16. Facebook Prophet/12. Python - Combining Events and Preparing Dataframe.mp4 17MB
  132. 17. Where To Go From Here/1. Thank You!.mp4 17MB
  133. 13. Gaussian Mixture/6. Python - Load Data.mp4 17MB
  134. 3. Basic Statistics/6. EXERCISE Python - Mean.mp4 16MB
  135. 5. Linear Regression/3. Linear Regression.mp4 16MB
  136. 9. Google Causal Impact (Econometrics and Causal Inference)/14. Correlation Recap and Stationarity.mp4 16MB
  137. 4. Intermediary Statistics/17. EXERCISE Python - Confidence Interval.mp4 16MB
  138. 12. RFM (Recency, Frequency, Monetary) Analysis/7. Python - Creating Sales Variable.mp4 16MB
  139. 9. Google Causal Impact (Econometrics and Causal Inference)/17. Python - Google Causal Impact Setup.mp4 16MB
  140. 4. Intermediary Statistics/25. Powerposing and p-hacking.mp4 16MB
  141. 12. RFM (Recency, Frequency, Monetary) Analysis/15. Python - Applying RFM Function.mp4 16MB
  142. 16. Facebook Prophet/32. Forecasting at Uber.mp4 16MB
  143. 10. Matching/12. Python - Other Variables.mp4 16MB
  144. 7. Logistic Regression/7. Python - Correlation Matrix.mp4 15MB
  145. 4. Intermediary Statistics/10. EXERCISE Python - Shapiro-Wilks.mp4 15MB
  146. 13. Gaussian Mixture/5. Python - Directory and Data.mp4 15MB
  147. 6. Multilinear Regression/18. Accuracy KPIs (Key Performance Indicators).mp4 15MB
  148. 16. Facebook Prophet/6. Python - Loading Data.mp4 14MB
  149. 12. RFM (Recency, Frequency, Monetary) Analysis/3. RFM Model.mp4 14MB
  150. 13. Gaussian Mixture/11. Python - Cluster Prediction and Assignment.mp4 14MB
  151. 16. Facebook Prophet/5. Python - Directory and Libraries.mp4 14MB
  152. 12. RFM (Recency, Frequency, Monetary) Analysis/5. Python - Directory and Libraries.mp4 14MB
  153. 9. Google Causal Impact (Econometrics and Causal Inference)/4. CASE STUDY Bitcoin Pricing (Briefing).mp4 14MB
  154. 10. Matching/2. Matching.mp4 14MB
  155. 15. Random Forest/5. Python - Directory and Libraries.mp4 14MB
  156. 6. Multilinear Regression/16. Python - Train and Test Split.mp4 14MB
  157. 13. Gaussian Mixture/3. Gaussian Mixture Model.mp4 14MB
  158. 15. Random Forest/7. Python - Transform Object into Numerical Variables.mp4 14MB
  159. 15. Random Forest/10. Python - Isolate X and Y.mp4 13MB
  160. 13. Gaussian Mixture/15. My Experience with Segmentation.mp4 13MB
  161. 4. Intermediary Statistics/2. Normal Distribution.mp4 13MB
  162. 16. Facebook Prophet/14. Python - Training and Test Set.mp4 13MB
  163. 3. Basic Statistics/11. EXERCISE Python - Mode.mp4 13MB
  164. 4. Intermediary Statistics/13. EXERCISE Python - Standard Error.mp4 13MB
  165. 3. Basic Statistics/18. CASE STUDY Moneyball.mp4 12MB
  166. 9. Google Causal Impact (Econometrics and Causal Inference)/10. Assumptions.mp4 12MB
  167. 5. Linear Regression/10. Dummy Variable Trap.mp4 12MB
  168. 13. Gaussian Mixture/7. Python - Transform Character variables.mp4 12MB
  169. 12. RFM (Recency, Frequency, Monetary) Analysis/13. Python - RFM Score.mp4 12MB
  170. 16. Facebook Prophet/3. Facebook Prophet.mp4 12MB
  171. 7. Logistic Regression/9. Python - Prepare X and Y.mp4 12MB
  172. 5. Linear Regression/6. Python - Adding Constant.mp4 11MB
  173. 10. Matching/24. Python - Outcome Visualization.mp4 11MB
  174. 5. Linear Regression/5. Python - Isolate X and Y.mp4 11MB
  175. 10. Matching/20. Python - Common Support Region Visualization.mp4 11MB
  176. 7. Logistic Regression/11. How to Read Logistic Regression Coefficients.mp4 11MB
  177. 16. Facebook Prophet/18. Python - Regressor Coefficients.mp4 11MB
  178. 16. Facebook Prophet/8. Python - Renaming Variables.mp4 10MB
  179. 13. Gaussian Mixture/8. AIC and BIC.mp4 10MB
  180. 7. Logistic Regression/3. Logistic Regression.mp4 10MB
  181. 16. Facebook Prophet/16. Additive vs. Multiplicative Seasonality.mp4 10MB
  182. 4. Intermediary Statistics/3. CASE STUDY Wine Quality (Briefing).mp4 10MB
  183. 6. Multilinear Regression/19. Python - Model Predictions.mp4 10MB
  184. 3. Basic Statistics/2. Arithmetic Mean.mp4 9MB
  185. 15. Random Forest/2. Ensemble Learning and Random Forest.mp4 9MB
  186. 12. RFM (Recency, Frequency, Monetary) Analysis/2. Value Based Segmentation.mp4 9MB
  187. 6. Multilinear Regression/6. Outliers.mp4 9MB
  188. 4. Intermediary Statistics/22. Chi-square test.mp4 9MB
  189. 13. Gaussian Mixture/10. Python - Gaussian Mixture Model.mp4 9MB
  190. 10. Matching/6. Unconfoundedness.mp4 8MB
  191. 4. Intermediary Statistics/14. Z-Score.mp4 8MB
  192. 3. Basic Statistics/7. Median and Mode.mp4 8MB
  193. 9. Google Causal Impact (Econometrics and Causal Inference)/5. Difference-in-Differences Framework.mp4 8MB
  194. 12. RFM (Recency, Frequency, Monetary) Analysis/10. Python - Monetary Variable.mp4 8MB
  195. 16. Facebook Prophet/2. Structural Time Series.mp4 8MB
  196. 4. Intermediary Statistics/11. Standard Error of the Mean.mp4 8MB
  197. 10. Matching/1. Matching - Game Plan.mp4 8MB
  198. 16. Facebook Prophet/15. Facebook Prophet Parameters.mp4 8MB
  199. 15. Random Forest/13. Python - Predictions.mp4 8MB
  200. 10. Matching/28. My Experience with Matching.mp4 8MB
  201. 15. Random Forest/16. Parameter Tuning.mp4 8MB
  202. 10. Matching/13. The Curse of Dimensionality.mp4 7MB
  203. 1. Introduction/2. Introduction.mp4 7MB
  204. 3. Basic Statistics/15. Standard Deviation.mp4 7MB
  205. 6. Multilinear Regression/13. Python - Adding Constant.mp4 7MB
  206. 15. Random Forest/9. Random Forest Quirks.mp4 7MB
  207. 10. Matching/22. Robustness Checks.mp4 7MB
  208. 4. Intermediary Statistics/18. T-test.mp4 7MB
  209. 3. Basic Statistics/17. EXERCISE Python - Standard Deviation.mp4 6MB
  210. 16. Facebook Prophet/9. Dynamic Holidays.mp4 6MB
  211. 16. Facebook Prophet/13. Training and Test Set.mp4 6MB
  212. 13. Gaussian Mixture/2. Clustering.mp4 6MB
  213. 4. Intermediary Statistics/8. Shapiro-Wilks Test.mp4 6MB
  214. 9. Google Causal Impact (Econometrics and Causal Inference)/6. Causal Impact Step-by-Step.mp4 6MB
  215. 9. Google Causal Impact (Econometrics and Causal Inference)/3. Time Series Data.mp4 6MB
  216. 6. Multilinear Regression/2. The Concept of Multilinear Regression.mp4 5MB
  217. 6. Multilinear Regression/14. Under and Over Fitting.mp4 5MB
  218. 10. Matching/3. CASE STUDY Catholic Schools & Standardized Tests (Briefing).mp4 5MB
  219. 6. Multilinear Regression/1. Multilinear Regression - Game Plan.mp4 4MB
  220. 16. Facebook Prophet/25. Parameters to tune.mp4 4MB
  221. 9. Google Causal Impact (Econometrics and Causal Inference)/2. Google Causal Impact - Game Plan.mp4 4MB
  222. 5. Linear Regression/1. Linear Regression - Game Plan.mp4 4MB
  223. 16. Facebook Prophet/1. Facebook Prophet - Game Plan.mp4 3MB
  224. 5. Linear Regression/2. CASE STUDY Diamonds (Briefing).mp4 3MB
  225. 15. Random Forest/1. Random Forest - Game Plan.mp4 3MB
  226. 7. Logistic Regression/1. Logistic Regression - Game Plan.mp4 3MB
  227. 6. Multilinear Regression/3. CASE STUDY Professors' Salary (Briefing).mp4 3MB
  228. 13. Gaussian Mixture/4. CASE STUDY Credit Cards #1 (Briefing).mp4 3MB
  229. 7. Logistic Regression/2. CASE STUDY Spam Emails (Briefing).mp4 3MB
  230. 12. RFM (Recency, Frequency, Monetary) Analysis/4. CASE STUDY Online Shopping (Briefing).mp4 3MB
  231. 3. Basic Statistics/1. Basic Statistics - Game Plan.mp4 3MB
  232. 16. Facebook Prophet/23. Cross-validation.mp4 3MB
  233. 6. Multilinear Regression/15. Training and Test Set.mp4 3MB
  234. 13. Gaussian Mixture/1. Gaussian Mixture - Game Plan.mp4 3MB
  235. 16. Facebook Prophet/4. CASE STUDY Wikipedia (Briefing).mp4 3MB
  236. 4. Intermediary Statistics/19. CASE STUDY Remote Work Predictions (Briefing).mp4 2MB
  237. 12. RFM (Recency, Frequency, Monetary) Analysis/1. RFM - Game Plan.mp4 2MB
  238. 15. Random Forest/4. CASE STUDY Credit Cards #2 (Briefing).mp4 2MB
  239. 3. Basic Statistics/3. CASE STUDY Moneyball (Briefing).mp4 2MB
  240. 4. Intermediary Statistics/1. Intermediary Statistics - Game Plan.mp4 2MB
  241. 13. Gaussian Mixture/14. CHALLENGE Solutions.srt 20KB
  242. 6. Multilinear Regression/22. CHALLENGE Solutions.srt 19KB
  243. 10. Matching/27. CHALLENGE Solutions.srt 16KB
  244. 7. Logistic Regression/20. CHALLENGE Solutions.srt 15KB
  245. 9. Google Causal Impact (Econometrics and Causal Inference)/22. CHALLENGE Solutions.srt 14KB
  246. 12. RFM (Recency, Frequency, Monetary) Analysis/18. CHALLENGE Solutions.srt 13KB
  247. 4. Intermediary Statistics/20. Python - T-test.srt 12KB
  248. 16. Facebook Prophet/30. CHALLENGE Solutions (Part 2).srt 12KB
  249. 3. Basic Statistics/13. Python - Correlation.srt 10KB
  250. 3. Basic Statistics/5. Python - Mean.srt 10KB
  251. 15. Random Forest/21. CHALLENGE Solutions (Part 2).srt 10KB
  252. 7. Logistic Regression/13. Python - Function to Read Coefficients.srt 10KB
  253. 16. Facebook Prophet/29. CHALLENGE Solutions (Part 1).srt 10KB
  254. 1. Introduction/5. Setting up the Course Material.srt 10KB
  255. 9. Google Causal Impact (Econometrics and Causal Inference)/15. Python - Stationarity.srt 10KB
  256. 3. Basic Statistics/4. Python - Directory, Libraries and Data.srt 10KB
  257. 15. Random Forest/20. CHALLENGE Solutions (Part 1).srt 9KB
  258. 4. Intermediary Statistics/5. Python - Normal Distribution Visualization.srt 9KB
  259. 13. Gaussian Mixture/12. Python - Interpretation.srt 9KB
  260. 16. Facebook Prophet/24. Python - Cross-validation.srt 9KB
  261. 4. Intermediary Statistics/9. Python - Shapiro-Wilks Test.srt 9KB
  262. 4. Intermediary Statistics/23. Python - Chi-square test.srt 9KB
  263. 10. Matching/18. Python - Logistic Regression and Debugging.srt 8KB
  264. 16. Facebook Prophet/31. CHALLENGE Solutions (Part 3).srt 8KB
  265. 7. Logistic Regression/6. Python - Histogram and Outlier Removal.srt 8KB
  266. 10. Matching/14. Python - Race Variable Transformation.srt 8KB
  267. 4. Intermediary Statistics/16. Python - Confidence Interval.srt 8KB
  268. 10. Matching/23. Python - Robustness Check - Repeated experiments.srt 8KB
  269. 15. Random Forest/18. Python - Parameter Tuning.srt 8KB
  270. 16. Facebook Prophet/27. Python - Parameter Tuning.srt 7KB
  271. 7. Logistic Regression/17. Python - Manual Accuracy Assessment.srt 7KB
  272. 7. Logistic Regression/15. Confusion Matrix.srt 7KB
  273. 12. RFM (Recency, Frequency, Monetary) Analysis/12. Python - Quartiles.srt 7KB
  274. 9. Google Causal Impact (Econometrics and Causal Inference)/21. CHALLENGE Introduction.srt 7KB
  275. 4. Intermediary Statistics/6. EXERCISE Python - Normal Distribution.srt 7KB
  276. 4. Intermediary Statistics/7. P-value.srt 7KB
  277. 16. Facebook Prophet/22. Python - Visualization.srt 7KB
  278. 13. Gaussian Mixture/9. Python - Optimal Number of Clusters.srt 7KB
  279. 6. Multilinear Regression/20. Python - Accuracy Assessment.srt 7KB
  280. 5. Linear Regression/12. EXERCISE Python - Linear Regression.srt 6KB
  281. 10. Matching/26. CHALLENGE Introduction.srt 6KB
  282. 4. Intermediary Statistics/15. Confidence interval.srt 6KB
  283. 9. Google Causal Impact (Econometrics and Causal Inference)/12. Python - Preparing DataFrame.srt 6KB
  284. 12. RFM (Recency, Frequency, Monetary) Analysis/3. RFM Model.srt 6KB
  285. 9. Google Causal Impact (Econometrics and Causal Inference)/9. Python - Bitcoin Price loading.srt 6KB
  286. 4. Intermediary Statistics/21. EXERCISE Python - T-test.srt 6KB
  287. 1. Introduction/3. Join Our Online Classroom!.srt 6KB
  288. 6. Multilinear Regression/4. Python - Preparing Script and Loading Data.srt 6KB
  289. 4. Intermediary Statistics/4. Python - Preparing Script and Loading Data.srt 6KB
  290. 10. Matching/19. Python - Preparing for Common Support Region.srt 6KB
  291. 10. Matching/15. Python - Education Variables.srt 6KB
  292. 16. Facebook Prophet/10. Python - Easter Holidays.srt 6KB
  293. 9. Google Causal Impact (Econometrics and Causal Inference)/20. Python - Impact Results.srt 6KB
  294. 16. Facebook Prophet/28. CHALLENGE Introduction.srt 6KB
  295. 5. Linear Regression/4. Python - Preparing Script and Loading Data.srt 6KB
  296. 5. Linear Regression/3. Linear Regression.srt 6KB
  297. 1. Introduction/6. The Modern Day Business Analyst.srt 6KB
  298. 7. Logistic Regression/16. Python - Confusion Matrix.srt 5KB
  299. 6. Multilinear Regression/7. Python - Plotting Continuous Variables.srt 5KB
  300. 3. Basic Statistics/12. Correlation.srt 5KB
  301. 16. Facebook Prophet/32. Forecasting at Uber.srt 5KB
  302. 6. Multilinear Regression/21. CHALLENGE Introduction.srt 5KB
  303. 10. Matching/9. Python - T-Test Loop.srt 5KB
  304. 6. Multilinear Regression/17. Python - Multilinear Regression.srt 5KB
  305. 10. Matching/21. Python - Matching.srt 5KB
  306. 16. Facebook Prophet/17. Facebook Prophet Model.srt 5KB
  307. 3. Basic Statistics/8. Python - Median.srt 5KB
  308. 13. Gaussian Mixture/13. CHALLENGE Introduction.srt 5KB
  309. 12. RFM (Recency, Frequency, Monetary) Analysis/16. Python - Results Summary.srt 5KB
  310. 6. Multilinear Regression/10. Python - For Loop.srt 5KB
  311. 10. Matching/11. Python - Chi-square Loop.srt 5KB
  312. 15. Random Forest/15. Python - Feature Importance.srt 5KB
  313. 6. Multilinear Regression/9. Python - Categorical Variables.srt 5KB
  314. 7. Logistic Regression/19. CHALLENGE Introduction.srt 5KB
  315. 16. Facebook Prophet/19. Python - Future Dataframe.srt 5KB
  316. 7. Logistic Regression/4. Python - Preparing Script and Loading Data.srt 5KB
  317. 12. RFM (Recency, Frequency, Monetary) Analysis/14. Python - RFM Function.srt 5KB
  318. 15. Random Forest/19. CHALLENGE Introduction.srt 5KB
  319. 4. Intermediary Statistics/12. Python - Standard Error.srt 5KB
  320. 9. Google Causal Impact (Econometrics and Causal Inference)/14. Correlation Recap and Stationarity.srt 5KB
  321. 15. Random Forest/3. How Decision Trees Work.srt 5KB
  322. 10. Matching/8. Python - T-Test.srt 5KB
  323. 5. Linear Regression/9. Python - Plotting Regression.srt 5KB
  324. 9. Google Causal Impact (Econometrics and Causal Inference)/23. EXERCISE Imposter Syndrome.srt 4KB
  325. 9. Google Causal Impact (Econometrics and Causal Inference)/1. Why Econometrics and Causal Inference.srt 4KB
  326. 9. Google Causal Impact (Econometrics and Causal Inference)/19. Interpretation of Results.srt 4KB
  327. 13. Gaussian Mixture/3. Gaussian Mixture Model.srt 4KB
  328. 9. Google Causal Impact (Econometrics and Causal Inference)/7. Python - Installing and Importing Libraries.srt 4KB
  329. 6. Multilinear Regression/12. Python - Isolate X and Y.srt 4KB
  330. 16. Facebook Prophet/26. Python - Parameter Grid.srt 4KB
  331. 3. Basic Statistics/18. CASE STUDY Moneyball.srt 4KB
  332. 3. Basic Statistics/14. EXERCISE Python - Correlation.srt 4KB
  333. 10. Matching/17. Common Support Region.srt 4KB
  334. 10. Matching/10. Python - Chi-square Test.srt 4KB
  335. 9. Google Causal Impact (Econometrics and Causal Inference)/11. Python - Load Control Groups.srt 4KB
  336. 9. Google Causal Impact (Econometrics and Causal Inference)/8. Python - Defining Dates.srt 4KB
  337. 16. Facebook Prophet/3. Facebook Prophet.srt 4KB
  338. 5. Linear Regression/11. Python - Dummy Variable.srt 4KB
  339. 12. RFM (Recency, Frequency, Monetary) Analysis/9. Python - Customer Level Aggregation.srt 4KB
  340. 4. Intermediary Statistics/25. Powerposing and p-hacking.srt 4KB
  341. 12. RFM (Recency, Frequency, Monetary) Analysis/17. CHALLENGE Introduction.srt 4KB
  342. 10. Matching/25. Python - Robustness Check - Removing 1 Confounder.srt 4KB
  343. 9. Google Causal Impact (Econometrics and Causal Inference)/18. Python - Google Causal Impact.srt 4KB
  344. 12. RFM (Recency, Frequency, Monetary) Analysis/8. Python - Date Variable.srt 4KB
  345. 5. Linear Regression/10. Dummy Variable Trap.srt 4KB
  346. 13. Gaussian Mixture/15. My Experience with Segmentation.srt 4KB
  347. 16. Facebook Prophet/21. Python - Accuracy Assessment.srt 4KB
  348. 5. Linear Regression/7. Linear Regression Output.srt 4KB
  349. 1. Introduction/4. Exercise Meet Your Classmates + Instructor.html 4KB
  350. 3. Basic Statistics/9. EXERCISE Python - Median.srt 4KB
  351. 15. Random Forest/14. Python - Classification Report and F1 score.srt 4KB
  352. 4. Intermediary Statistics/24. EXERCISE Python - Chi-square.srt 4KB
  353. 16. Facebook Prophet/14. Python - Training and Test Set.srt 4KB
  354. 10. Matching/16. Python - Cleaning and Preparing Dataset.srt 4KB
  355. 5. Linear Regression/8. Python - Linear Regression model and summary.srt 4KB
  356. 7. Logistic Regression/14. Python - Predictions.srt 4KB
  357. 15. Random Forest/17. Python - Parameter Grid.srt 4KB
  358. 6. Multilinear Regression/11. Python - Creating Dummy Variables.srt 4KB
  359. 1. Introduction/1. Python for Business Analytics & Intelligence.srt 3KB
  360. 6. Multilinear Regression/18. Accuracy KPIs (Key Performance Indicators).srt 3KB
  361. 4. Intermediary Statistics/2. Normal Distribution.srt 3KB
  362. 15. Random Forest/11. Python - Training and Test Set.srt 3KB
  363. 10. Matching/2. Matching.srt 3KB
  364. 6. Multilinear Regression/5. Python - Summary Statistics.srt 3KB
  365. 3. Basic Statistics/10. Python - Mode.srt 3KB
  366. 16. Facebook Prophet/11. Python - Black Friday.srt 3KB
  367. 12. RFM (Recency, Frequency, Monetary) Analysis/2. Value Based Segmentation.srt 3KB
  368. 6. Multilinear Regression/8. Python - Correlation Matrix.srt 3KB
  369. 9. Google Causal Impact (Econometrics and Causal Inference)/16. Python - Correlation.srt 3KB
  370. 7. Logistic Regression/5. Python - Summary Statistics.srt 3KB
  371. 6. Multilinear Regression/6. Outliers.srt 3KB
  372. 3. Basic Statistics/7. Median and Mode.srt 3KB
  373. 5. Linear Regression/6. Python - Adding Constant.srt 3KB
  374. 10. Matching/1. Matching - Game Plan.srt 3KB
  375. 4. Intermediary Statistics/10. EXERCISE Python - Shapiro-Wilks.srt 3KB
  376. 15. Random Forest/12. Python - Random Forest Model.srt 3KB
  377. 9. Google Causal Impact (Econometrics and Causal Inference)/10. Assumptions.srt 3KB
  378. 10. Matching/28. My Experience with Matching.srt 3KB
  379. 4. Intermediary Statistics/11. Standard Error of the Mean.srt 3KB
  380. 4. Intermediary Statistics/3. CASE STUDY Wine Quality (Briefing).srt 3KB
  381. 16. Facebook Prophet/7. Python - Transforming Date Variable.srt 3KB
  382. 13. Gaussian Mixture/11. Python - Cluster Prediction and Assignment.srt 3KB
  383. 10. Matching/4. Python - Directory and Libraries.srt 3KB
  384. 4. Intermediary Statistics/13. EXERCISE Python - Standard Error.srt 3KB
  385. 12. RFM (Recency, Frequency, Monetary) Analysis/6. Python - Loading Data.srt 3KB
  386. 15. Random Forest/16. Parameter Tuning.srt 3KB
  387. 4. Intermediary Statistics/14. Z-Score.srt 3KB
  388. 12. RFM (Recency, Frequency, Monetary) Analysis/11. Python - Tidying up Dataframe.srt 3KB
  389. 7. Logistic Regression/8. Python - Transforming Dependent Variable.srt 3KB
  390. 7. Logistic Regression/10. Python - Training and Test Set.srt 3KB
  391. 10. Matching/7. Python - Comparing Means.srt 3KB
  392. 4. Intermediary Statistics/22. Chi-square test.srt 3KB
  393. 7. Logistic Regression/18. Python - Classification Report.srt 3KB
  394. 7. Logistic Regression/11. How to Read Logistic Regression Coefficients.srt 3KB
  395. 16. Facebook Prophet/6. Python - Loading Data.srt 3KB
  396. 9. Google Causal Impact (Econometrics and Causal Inference)/13. Python - Preparing for Correlation Matrix.srt 3KB
  397. 16. Facebook Prophet/12. Python - Combining Events and Preparing Dataframe.srt 3KB
  398. 10. Matching/5. Python - Loading Data.srt 3KB
  399. 15. Random Forest/9. Random Forest Quirks.srt 3KB
  400. 16. Facebook Prophet/2. Structural Time Series.srt 3KB
  401. 16. Facebook Prophet/20. Python - Forecasting.srt 3KB
  402. 9. Google Causal Impact (Econometrics and Causal Inference)/4. CASE STUDY Bitcoin Pricing (Briefing).srt 3KB
  403. 16. Facebook Prophet/16. Additive vs. Multiplicative Seasonality.srt 3KB
  404. 3. Basic Statistics/15. Standard Deviation.srt 3KB
  405. 12. RFM (Recency, Frequency, Monetary) Analysis/15. Python - Applying RFM Function.srt 3KB
  406. 3. Basic Statistics/16. Python - Standard Deviation.srt 3KB
  407. 4. Intermediary Statistics/17. EXERCISE Python - Confidence Interval.srt 3KB
  408. 3. Basic Statistics/2. Arithmetic Mean.srt 3KB
  409. 6. Multilinear Regression/16. Python - Train and Test Split.srt 3KB
  410. 9. Google Causal Impact (Econometrics and Causal Inference)/6. Causal Impact Step-by-Step.srt 3KB
  411. 10. Matching/6. Unconfoundedness.srt 3KB
  412. 10. Matching/22. Robustness Checks.srt 3KB
  413. 7. Logistic Regression/12. Python - Logistic Regression.srt 3KB
  414. 7. Logistic Regression/7. Python - Correlation Matrix.srt 3KB
  415. 4. Intermediary Statistics/18. T-test.srt 3KB
  416. 15. Random Forest/8. Python - Summary Statistics.srt 3KB
  417. 7. Logistic Regression/9. Python - Prepare X and Y.srt 3KB
  418. 15. Random Forest/2. Ensemble Learning and Random Forest.srt 2KB
  419. 13. Gaussian Mixture/2. Clustering.srt 2KB
  420. 15. Random Forest/5. Python - Directory and Libraries.srt 2KB
  421. 16. Facebook Prophet/9. Dynamic Holidays.srt 2KB
  422. 9. Google Causal Impact (Econometrics and Causal Inference)/17. Python - Google Causal Impact Setup.srt 2KB
  423. 3. Basic Statistics/6. EXERCISE Python - Mean.srt 2KB
  424. 16. Facebook Prophet/5. Python - Directory and Libraries.srt 2KB
  425. 13. Gaussian Mixture/8. AIC and BIC.srt 2KB
  426. 1. Introduction/2. Introduction.srt 2KB
  427. 9. Google Causal Impact (Econometrics and Causal Inference)/5. Difference-in-Differences Framework.srt 2KB
  428. 12. RFM (Recency, Frequency, Monetary) Analysis/5. Python - Directory and Libraries.srt 2KB
  429. 16. Facebook Prophet/15. Facebook Prophet Parameters.srt 2KB
  430. 16. Facebook Prophet/13. Training and Test Set.srt 2KB
  431. 6. Multilinear Regression/2. The Concept of Multilinear Regression.srt 2KB
  432. 7. Logistic Regression/3. Logistic Regression.srt 2KB
  433. 13. Gaussian Mixture/5. Python - Directory and Data.srt 2KB
  434. 4. Intermediary Statistics/8. Shapiro-Wilks Test.srt 2KB
  435. 13. Gaussian Mixture/6. Python - Load Data.srt 2KB
  436. 15. Random Forest/6. Python - Loading Data.srt 2KB
  437. 11. PART C SEGMENTATION/1. What is Segmentation and why is it important.html 2KB
  438. 5. Linear Regression/5. Python - Isolate X and Y.srt 2KB
  439. 15. Random Forest/7. Python - Transform Object into Numerical Variables.srt 2KB
  440. 12. RFM (Recency, Frequency, Monetary) Analysis/13. Python - RFM Score.srt 2KB
  441. 12. RFM (Recency, Frequency, Monetary) Analysis/7. Python - Creating Sales Variable.srt 2KB
  442. 3. Basic Statistics/11. EXERCISE Python - Mode.srt 2KB
  443. 10. Matching/24. Python - Outcome Visualization.srt 2KB
  444. 10. Matching/13. The Curse of Dimensionality.srt 2KB
  445. 10. Matching/12. Python - Other Variables.srt 2KB
  446. 17. Where To Go From Here/1. Thank You!.srt 2KB
  447. 6. Multilinear Regression/1. Multilinear Regression - Game Plan.srt 2KB
  448. 15. Random Forest/10. Python - Isolate X and Y.srt 2KB
  449. 10. Matching/20. Python - Common Support Region Visualization.srt 2KB
  450. 8. PART B ECONOMETRICS & CAUSAL INFERENCE/1. What are Econometrics & Causal Inference, and why are they important.html 2KB
  451. 6. Multilinear Regression/19. Python - Model Predictions.srt 2KB
  452. 16. Facebook Prophet/25. Parameters to tune.srt 2KB
  453. 16. Facebook Prophet/8. Python - Renaming Variables.srt 2KB
  454. 5. Linear Regression/1. Linear Regression - Game Plan.srt 2KB
  455. 16. Facebook Prophet/18. Python - Regressor Coefficients.srt 2KB
  456. 6. Multilinear Regression/14. Under and Over Fitting.srt 2KB
  457. 9. Google Causal Impact (Econometrics and Causal Inference)/3. Time Series Data.srt 2KB
  458. 14. PART D PREDICTIVE ANALYTICS/1. What are Predictive Analytics and why are they important.html 2KB
  459. 6. Multilinear Regression/13. Python - Adding Constant.srt 2KB
  460. 1. Introduction/7. Monthly Coding Challenges, Free Resources and Guides.html 2KB
  461. 2. PART A STATISTICS/1. What are Statistics and why are they important.html 2KB
  462. 16. Facebook Prophet/1. Facebook Prophet - Game Plan.srt 2KB
  463. 15. Random Forest/13. Python - Predictions.srt 1KB
  464. 9. Google Causal Impact (Econometrics and Causal Inference)/2. Google Causal Impact - Game Plan.srt 1KB
  465. 13. Gaussian Mixture/1. Gaussian Mixture - Game Plan.srt 1KB
  466. 7. Logistic Regression/1. Logistic Regression - Game Plan.srt 1KB
  467. 17. Where To Go From Here/3. Endorsements On LinkedIn.html 1KB
  468. 13. Gaussian Mixture/10. Python - Gaussian Mixture Model.srt 1KB
  469. 12. RFM (Recency, Frequency, Monetary) Analysis/10. Python - Monetary Variable.srt 1KB
  470. 13. Gaussian Mixture/7. Python - Transform Character variables.srt 1KB
  471. 3. Basic Statistics/17. EXERCISE Python - Standard Deviation.srt 1KB
  472. 3. Basic Statistics/1. Basic Statistics - Game Plan.srt 1KB
  473. 3. Basic Statistics/3. CASE STUDY Moneyball (Briefing).srt 1KB
  474. 18. BONUS Section/1. Special Bonus Lecture.html 1KB
  475. 15. Random Forest/1. Random Forest - Game Plan.srt 1KB
  476. 10. Matching/3. CASE STUDY Catholic Schools & Standardized Tests (Briefing).srt 1KB
  477. 6. Multilinear Regression/15. Training and Test Set.srt 1KB
  478. 16. Facebook Prophet/23. Cross-validation.srt 1KB
  479. 5. Linear Regression/2. CASE STUDY Diamonds (Briefing).srt 1KB
  480. 7. Logistic Regression/2. CASE STUDY Spam Emails (Briefing).srt 1KB
  481. 12. RFM (Recency, Frequency, Monetary) Analysis/4. CASE STUDY Online Shopping (Briefing).srt 1KB
  482. 13. Gaussian Mixture/4. CASE STUDY Credit Cards #1 (Briefing).srt 1KB
  483. 6. Multilinear Regression/3. CASE STUDY Professors' Salary (Briefing).srt 1019B
  484. 16. Facebook Prophet/4. CASE STUDY Wikipedia (Briefing).srt 975B
  485. 4. Intermediary Statistics/1. Intermediary Statistics - Game Plan.srt 971B
  486. 17. Where To Go From Here/2. Become An Alumni.html 921B
  487. 4. Intermediary Statistics/19. CASE STUDY Remote Work Predictions (Briefing).srt 875B
  488. 15. Random Forest/4. CASE STUDY Credit Cards #2 (Briefing).srt 860B
  489. 17. Where To Go From Here/5. Coding Challenges.html 860B
  490. 12. RFM (Recency, Frequency, Monetary) Analysis/1. RFM - Game Plan.srt 849B
  491. 17. Where To Go From Here/4. Learning Guideline.html 353B
  492. 0. Websites you may like/[CourseClub.Me].url 122B
  493. 1. Introduction/[CourseClub.Me].url 122B
  494. 12. RFM (Recency, Frequency, Monetary) Analysis/[CourseClub.Me].url 122B
  495. 16. Facebook Prophet/[CourseClub.Me].url 122B
  496. 6. Multilinear Regression/[CourseClub.Me].url 122B
  497. [CourseClub.Me].url 122B
  498. 1. Introduction/5.1 Course Materials.html 99B
  499. 1. Introduction/5.2 Sign up for your free Google Drive account here..html 85B
  500. 0. Websites you may like/[GigaCourse.Com].url 49B
  501. 1. Introduction/[GigaCourse.Com].url 49B
  502. 12. RFM (Recency, Frequency, Monetary) Analysis/[GigaCourse.Com].url 49B
  503. 16. Facebook Prophet/[GigaCourse.Com].url 49B
  504. 6. Multilinear Regression/[GigaCourse.Com].url 49B
  505. [GigaCourse.Com].url 49B