589689.xyz

[] Udemy - Machine Learning Practical 6 Real-World Applications

  • 收录时间:2019-12-20 10:48:41
  • 文件大小:4GB
  • 下载次数:204
  • 最近下载:2021-01-23 05:44:53
  • 磁力链接:
立即下载 复制链接

文件列表

  1. 2. Breast Cancer Classification/8. Improving the Model.mp4 190MB
  2. 2. Breast Cancer Classification/5. Data Visualisation.mp4 140MB
  3. 3. Fashion Class Classification/3. Data Visualisation.mp4 130MB
  4. 3. Fashion Class Classification/7. Model Training Part IV.mp4 128MB
  5. 3. Fashion Class Classification/6. Model Training Part III.mp4 126MB
  6. 3. Fashion Class Classification/4. Model Training Part I.mp4 104MB
  7. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/2. Data.mp4 102MB
  8. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/12. Grid Search Part 2.mp4 98MB
  9. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/10. Model Building Part 2.mp4 93MB
  10. 3. Fashion Class Classification/1. Business Challenge.mp4 92MB
  11. 2. Breast Cancer Classification/7. Model Evaluation.mp4 91MB
  12. 5. Minimizing Churn Rate Through Analysis of Financial Habits/9. Feature Scaling & Balancing.mp4 80MB
  13. 2. Breast Cancer Classification/4. Challenge in Machine Learning Vocabulary.mp4 79MB
  14. 3. Fashion Class Classification/5. Model Training Part II.mp4 78MB
  15. 5. Minimizing Churn Rate Through Analysis of Financial Habits/2. Data.mp4 77MB
  16. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/1. Introduction.mp4 75MB
  17. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/11. Grid Search Part 1.mp4 74MB
  18. 3. Fashion Class Classification/8. Model Evaluation.mp4 74MB
  19. 4. Directing Customers to Subscription Through App Behavior Analysis/10. Model Building.mp4 72MB
  20. 4. Directing Customers to Subscription Through App Behavior Analysis/8. Feature Engineering - Screens.mp4 71MB
  21. 2. Breast Cancer Classification/6. Model Training.mp4 71MB
  22. 5. Minimizing Churn Rate Through Analysis of Financial Habits/5. Pie Chart Distributions.mp4 71MB
  23. 3. Fashion Class Classification/2. Challenge in Machine Learning Vocabulary.mp4 69MB
  24. 5. Minimizing Churn Rate Through Analysis of Financial Habits/12. Feature Selection.mp4 64MB
  25. 2. Breast Cancer Classification/2. Business Challenge.mp4 61MB
  26. 4. Directing Customers to Subscription Through App Behavior Analysis/4. Features Histograms.mp4 61MB
  27. 4. Directing Customers to Subscription Through App Behavior Analysis/9. Data Pre-Processing.mp4 61MB
  28. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/8. Data Preprocessing.mp4 60MB
  29. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/9. Model Building Part 1.mp4 59MB
  30. 2. Breast Cancer Classification/3. Updates on Udemy Reviews.mp4 56MB
  31. 5. Minimizing Churn Rate Through Analysis of Financial Habits/7. Correlation Matrix.mp4 56MB
  32. 3. Fashion Class Classification/10. Conclusion.mp4 55MB
  33. 4. Directing Customers to Subscription Through App Behavior Analysis/7. Feature Engineering - Response.mp4 55MB
  34. 4. Directing Customers to Subscription Through App Behavior Analysis/3. Data.mp4 54MB
  35. 5. Minimizing Churn Rate Through Analysis of Financial Habits/10. Model Building.mp4 51MB
  36. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/4. Histograms.mp4 51MB
  37. 5. Minimizing Churn Rate Through Analysis of Financial Habits/4. Features Histograms.mp4 50MB
  38. 5. Minimizing Churn Rate Through Analysis of Financial Habits/6. Correlation Plot.mp4 49MB
  39. 7. Credit Card Fraud Detection/7. Deep Learning Part 2.mp4 48MB
  40. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/3. Data Housekeeping.mp4 44MB
  41. 5. Minimizing Churn Rate Through Analysis of Financial Habits/8. One-Hot Encoding.mp4 43MB
  42. 7. Credit Card Fraud Detection/11. Confusion Matrix.mp4 40MB
  43. 7. Credit Card Fraud Detection/5. Data Preprocessing.mp4 39MB
  44. 5. Minimizing Churn Rate Through Analysis of Financial Habits/13. Model Conclusion.mp4 38MB
  45. 7. Credit Card Fraud Detection/8. Splitting the Data.mp4 38MB
  46. 7. Credit Card Fraud Detection/16. Undersampling.mp4 37MB
  47. 1. Introduction/1. Welcome to the course!.mp4 37MB
  48. 7. Credit Card Fraud Detection/17. Smote.mp4 36MB
  49. 7. Credit Card Fraud Detection/12. Machine Learning Classifiers.mp4 34MB
  50. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/6. Correlation Matrix.mp4 33MB
  51. 5. Minimizing Churn Rate Through Analysis of Financial Habits/3. Data Cleaning.mp4 33MB
  52. 4. Directing Customers to Subscription Through App Behavior Analysis/6. Correlation Matrix.mp4 32MB
  53. 5. Minimizing Churn Rate Through Analysis of Financial Habits/11. K-Fold Cross Validation.mp4 32MB
  54. 3. Fashion Class Classification/9. Improving the Model.mp4 32MB
  55. 7. Credit Card Fraud Detection/13. Random Forest.mp4 31MB
  56. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/14. Final Remarks.mp4 31MB
  57. 7. Credit Card Fraud Detection/1. Case Study.mp4 30MB
  58. 4. Directing Customers to Subscription Through App Behavior Analysis/11. Model Conclusion.mp4 30MB
  59. 5. Minimizing Churn Rate Through Analysis of Financial Habits/14. Final Remarks.mp4 24MB
  60. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/5. Correlation Plot.mp4 24MB
  61. 2. Breast Cancer Classification/9. Conclusion.mp4 24MB
  62. 7. Credit Card Fraud Detection/3. Set Up.mp4 24MB
  63. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/7. Feature Engineering.mp4 23MB
  64. 7. Credit Card Fraud Detection/6. Deep Learning Part 1.mp4 23MB
  65. 7. Credit Card Fraud Detection/2. Machine Learning Vocabulary.mp4 23MB
  66. 4. Directing Customers to Subscription Through App Behavior Analysis/5. Correlation Plot.mp4 22MB
  67. 7. Credit Card Fraud Detection/9. Training.mp4 21MB
  68. 7. Credit Card Fraud Detection/4. Data Visualization.mp4 20MB
  69. 5. Minimizing Churn Rate Through Analysis of Financial Habits/1. Introduction.mp4 20MB
  70. 7. Credit Card Fraud Detection/18. Final remarks.mp4 19MB
  71. 4. Directing Customers to Subscription Through App Behavior Analysis/12. Final Remarks.mp4 19MB
  72. 7. Credit Card Fraud Detection/14. Decision Trees.mp4 19MB
  73. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/13. Model Conclusion.mp4 18MB
  74. 4. Directing Customers to Subscription Through App Behavior Analysis/2. Introduction.mp4 18MB
  75. 7. Credit Card Fraud Detection/10. Metrics.mp4 15MB
  76. 2. Breast Cancer Classification/1. Introduction.mp4 15MB
  77. 4. Directing Customers to Subscription Through App Behavior Analysis/1. Fintech Case Studies Introduction.mp4 15MB
  78. 7. Credit Card Fraud Detection/15. Sampling.mp4 8MB
  79. 2. Breast Cancer Classification/8. Improving the Model.vtt 29KB
  80. 2. Breast Cancer Classification/5. Data Visualisation.vtt 23KB
  81. 3. Fashion Class Classification/3. Data Visualisation.vtt 20KB
  82. 3. Fashion Class Classification/7. Model Training Part IV.vtt 19KB
  83. 3. Fashion Class Classification/6. Model Training Part III.vtt 14KB
  84. 2. Breast Cancer Classification/7. Model Evaluation.vtt 14KB
  85. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/11. Grid Search Part 1.vtt 14KB
  86. 4. Directing Customers to Subscription Through App Behavior Analysis/10. Model Building.vtt 13KB
  87. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/4. Histograms.vtt 13KB
  88. 3. Fashion Class Classification/8. Model Evaluation.vtt 12KB
  89. 3. Fashion Class Classification/4. Model Training Part I.vtt 12KB
  90. 5. Minimizing Churn Rate Through Analysis of Financial Habits/7. Correlation Matrix.vtt 12KB
  91. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/10. Model Building Part 2.vtt 12KB
  92. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/12. Grid Search Part 2.vtt 11KB
  93. 2. Breast Cancer Classification/6. Model Training.vtt 11KB
  94. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/8. Data Preprocessing.vtt 11KB
  95. 5. Minimizing Churn Rate Through Analysis of Financial Habits/9. Feature Scaling & Balancing.vtt 11KB
  96. 5. Minimizing Churn Rate Through Analysis of Financial Habits/4. Features Histograms.vtt 11KB
  97. 5. Minimizing Churn Rate Through Analysis of Financial Habits/5. Pie Chart Distributions.vtt 11KB
  98. 4. Directing Customers to Subscription Through App Behavior Analysis/8. Feature Engineering - Screens.vtt 10KB
  99. 3. Fashion Class Classification/5. Model Training Part II.vtt 10KB
  100. 2. Breast Cancer Classification/4. Challenge in Machine Learning Vocabulary.vtt 10KB
  101. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/2. Data.vtt 10KB
  102. 4. Directing Customers to Subscription Through App Behavior Analysis/9. Data Pre-Processing.vtt 10KB
  103. 5. Minimizing Churn Rate Through Analysis of Financial Habits/2. Data.vtt 10KB
  104. 4. Directing Customers to Subscription Through App Behavior Analysis/4. Features Histograms.vtt 10KB
  105. 4. Directing Customers to Subscription Through App Behavior Analysis/7. Feature Engineering - Response.vtt 10KB
  106. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/1. Introduction.vtt 10KB
  107. 5. Minimizing Churn Rate Through Analysis of Financial Habits/10. Model Building.vtt 9KB
  108. 5. Minimizing Churn Rate Through Analysis of Financial Habits/6. Correlation Plot.vtt 9KB
  109. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/6. Correlation Matrix.vtt 9KB
  110. 5. Minimizing Churn Rate Through Analysis of Financial Habits/12. Feature Selection.vtt 9KB
  111. 3. Fashion Class Classification/2. Challenge in Machine Learning Vocabulary.vtt 8KB
  112. 4. Directing Customers to Subscription Through App Behavior Analysis/6. Correlation Matrix.vtt 8KB
  113. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/9. Model Building Part 1.vtt 8KB
  114. 7. Credit Card Fraud Detection/12. Machine Learning Classifiers.vtt 8KB
  115. 7. Credit Card Fraud Detection/7. Deep Learning Part 2.vtt 7KB
  116. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/3. Data Housekeeping.vtt 7KB
  117. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/5. Correlation Plot.vtt 7KB
  118. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/7. Feature Engineering.vtt 7KB
  119. 5. Minimizing Churn Rate Through Analysis of Financial Habits/8. One-Hot Encoding.vtt 7KB
  120. 3. Fashion Class Classification/1. Business Challenge.vtt 6KB
  121. 5. Minimizing Churn Rate Through Analysis of Financial Habits/3. Data Cleaning.vtt 6KB
  122. 4. Directing Customers to Subscription Through App Behavior Analysis/5. Correlation Plot.vtt 6KB
  123. 5. Minimizing Churn Rate Through Analysis of Financial Habits/13. Model Conclusion.vtt 5KB
  124. 5. Minimizing Churn Rate Through Analysis of Financial Habits/11. K-Fold Cross Validation.vtt 5KB
  125. 3. Fashion Class Classification/10. Conclusion.vtt 5KB
  126. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/14. Final Remarks.vtt 4KB
  127. 7. Credit Card Fraud Detection/8. Splitting the Data.vtt 4KB
  128. 4. Directing Customers to Subscription Through App Behavior Analysis/11. Model Conclusion.vtt 4KB
  129. 4. Directing Customers to Subscription Through App Behavior Analysis/3. Data.vtt 4KB
  130. 7. Credit Card Fraud Detection/11. Confusion Matrix.vtt 4KB
  131. 7. Credit Card Fraud Detection/10. Metrics.vtt 4KB
  132. 2. Breast Cancer Classification/2. Business Challenge.vtt 4KB
  133. 2. Breast Cancer Classification/9. Conclusion.vtt 4KB
  134. 2. Breast Cancer Classification/3. Updates on Udemy Reviews.vtt 4KB
  135. 7. Credit Card Fraud Detection/1. Case Study.vtt 4KB
  136. 3. Fashion Class Classification/9. Improving the Model.vtt 3KB
  137. 7. Credit Card Fraud Detection/6. Deep Learning Part 1.vtt 3KB
  138. 6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/13. Model Conclusion.vtt 3KB
  139. 7. Credit Card Fraud Detection/2. Machine Learning Vocabulary.vtt 3KB
  140. 7. Credit Card Fraud Detection/3. Set Up.vtt 3KB
  141. 5. Minimizing Churn Rate Through Analysis of Financial Habits/14. Final Remarks.vtt 3KB
  142. 7. Credit Card Fraud Detection/13. Random Forest.vtt 3KB
  143. 7. Credit Card Fraud Detection/18. Final remarks.vtt 3KB
  144. 7. Credit Card Fraud Detection/5. Data Preprocessing.vtt 3KB
  145. 7. Credit Card Fraud Detection/14. Decision Trees.vtt 3KB
  146. 7. Credit Card Fraud Detection/16. Undersampling.vtt 3KB
  147. 5. Minimizing Churn Rate Through Analysis of Financial Habits/1. Introduction.vtt 3KB
  148. 7. Credit Card Fraud Detection/17. Smote.vtt 2KB
  149. 4. Directing Customers to Subscription Through App Behavior Analysis/12. Final Remarks.vtt 2KB
  150. 7. Credit Card Fraud Detection/4. Data Visualization.vtt 2KB
  151. 1. Introduction/1. Welcome to the course!.vtt 2KB
  152. 4. Directing Customers to Subscription Through App Behavior Analysis/2. Introduction.vtt 2KB
  153. 7. Credit Card Fraud Detection/15. Sampling.vtt 2KB
  154. 4. Directing Customers to Subscription Through App Behavior Analysis/1. Fintech Case Studies Introduction.vtt 2KB
  155. 7. Credit Card Fraud Detection/9. Training.vtt 2KB
  156. [FTU Forum].url 1KB
  157. 2. Breast Cancer Classification/1. Introduction.vtt 1KB
  158. [FreeCoursesOnline.Me].url 133B
  159. [FreeTutorials.Eu].url 129B
  160. 1. Introduction/2. Where to get the materials.html 128B