[FreeCourseSite.com] Udemy - Machine Learning with Imbalanced Data

File Type Create Time File Size Seeders Leechers Updated
Movie 2021-05-17 2.95GB 2 0 1 month ago
Download
Magnet link   or   Save Instantly without Torrenting   or   Torrent download

To download this file, you need a free bitTorrent client such as qBittorrent.

Report Abuse
Tags
FreeCourseSite  com  Udemy  Machine  Learning  with  Imbalanced  Data  
Related Torrents
  1. [FreeCourseSite.com] Udemy - Machine Learning Natural Language Processing in Python (V2) 6.67GB
  2. [FreeCourseSite.com] Udemy - Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 3.89GB
  3. [FreeCourseSite.com] Udemy - Machine Learning Essentials (2023) - Master core ML concepts 15.85GB
  4. [ DevCourseWeb.com ] Udemy - Machine Learning Mastery - From Data to Advanced Classifiers 2.53GB
  5. [GigaCourse.Com] Udemy - Machine Learning, Data Science and Generative AI with Python 7.21GB
  6. [ DevCourseWeb.com ] Active Machine Learning with Python - Refine and elevate data quality over quantity with active learning (True EPUB) 8.68MB
  7. Abdelaziz Mounir, Abhishek Kumar - Machine Learning for Imbalanced Data - 2023 27.71MB
  8. [ TutGator.com ] Udemy - Machine Learning - Practical labs with Math's Core Foundation 906.86MB
  9. [ FreeCourseWeb.com ] Udemy - Machine Learning On Google Cloud - Sequence And Text Models 1.65GB
  10. [FreeCourseSite.com] Udemy - Testing React with Jest and React Testing Library (RTL) 2.63GB
Files
  1. 0. Websites you may like/[CourseClub.ME].url 122B
  2. 0. Websites you may like/[FCS Forum].url 133B
  3. 0. Websites you may like/[FreeCourseSite.com].url 127B
  4. 1. Introduction/1. Introduction.mp4 32.25MB
  5. 1. Introduction/1. Introduction.srt 4.04KB
  6. 1. Introduction/2. Course Curriculum Overview.mp4 17.54MB
  7. 1. Introduction/2. Course Curriculum Overview.srt 3.90KB
  8. 1. Introduction/3. Course Material.mp4 10.96MB
  9. 1. Introduction/3. Course Material.srt 2.36KB
  10. 1. Introduction/4. Code Jupyter notebooks.html 962B
  11. 1. Introduction/5. Presentations covered in the course.html 286B
  12. 1. Introduction/6. Python package Imbalanced-learn.html 699B
  13. 1. Introduction/7. Download Datasets.html 354B
  14. 1. Introduction/8. Additional resources for Machine Learning and Python programming.html 2.61KB
  15. 10. Moving Forward/1. Next steps.html 712B
  16. 2. Machine Learning with Imbalanced Data Overview/1. Imbalanced classes - Introduction.mp4 33.30MB
  17. 2. Machine Learning with Imbalanced Data Overview/1. Imbalanced classes - Introduction.srt 6.47KB
  18. 2. Machine Learning with Imbalanced Data Overview/2. Nature of the imbalanced class.mp4 35.11MB
  19. 2. Machine Learning with Imbalanced Data Overview/2. Nature of the imbalanced class.srt 5.93KB
  20. 2. Machine Learning with Imbalanced Data Overview/3. Approaches to work with imbalanced datasets - Overview.mp4 20.24MB
  21. 2. Machine Learning with Imbalanced Data Overview/3. Approaches to work with imbalanced datasets - Overview.srt 4.68KB
  22. 2. Machine Learning with Imbalanced Data Overview/4. Additional Reading Resources (Optional).html 1.04KB
  23. 3. Evaluation Metrics/1. Introduction to Performance Metrics.mp4 10.79MB
  24. 3. Evaluation Metrics/1. Introduction to Performance Metrics.srt 3.30KB
  25. 3. Evaluation Metrics/10. Geometric Mean, Dominance, Index of Imbalanced Accuracy - Demo.mp4 86.77MB
  26. 3. Evaluation Metrics/10. Geometric Mean, Dominance, Index of Imbalanced Accuracy - Demo.srt 12.25KB
  27. 3. Evaluation Metrics/11. ROC-AUC.mp4 39.25MB
  28. 3. Evaluation Metrics/11. ROC-AUC.srt 8.34KB
  29. 3. Evaluation Metrics/12. ROC-AUC - Demo.mp4 31.56MB
  30. 3. Evaluation Metrics/12. ROC-AUC - Demo.srt 5.33KB
  31. 3. Evaluation Metrics/13. Precision-Recall Curve.mp4 40.50MB
  32. 3. Evaluation Metrics/13. Precision-Recall Curve.srt 9.24KB
  33. 3. Evaluation Metrics/14. Precision-Recall Curve - Demo.mp4 18.08MB
  34. 3. Evaluation Metrics/14. Precision-Recall Curve - Demo.srt 3.41KB
  35. 3. Evaluation Metrics/15. Additional reading resources (Optional).html 1.60KB
  36. 3. Evaluation Metrics/16. Probability.mp4 20.64MB
  37. 3. Evaluation Metrics/16. Probability.srt 5.54KB
  38. 3. Evaluation Metrics/16.1 Link to Jupyter notebook.html 177B
  39. 3. Evaluation Metrics/2. Accuracy.mp4 21.44MB
  40. 3. Evaluation Metrics/2. Accuracy.srt 5.32KB
  41. 3. Evaluation Metrics/3. Accuracy - Demo.mp4 47.61MB
  42. 3. Evaluation Metrics/3. Accuracy - Demo.srt 7.28KB
  43. 3. Evaluation Metrics/4. Precision, Recall and F-measure.mp4 66.98MB
  44. 3. Evaluation Metrics/4. Precision, Recall and F-measure.srt 15.12KB
  45. 3. Evaluation Metrics/5. Install Yellowbrick.html 684B
  46. 3. Evaluation Metrics/6. Precision, Recall and F-measure - Demo.mp4 80.33MB
  47. 3. Evaluation Metrics/6. Precision, Recall and F-measure - Demo.srt 12.20KB
  48. 3. Evaluation Metrics/7. Confusion tables, FPR and FNR.mp4 29.72MB
  49. 3. Evaluation Metrics/7. Confusion tables, FPR and FNR.srt 7.37KB
  50. 3. Evaluation Metrics/8. Confusion tables, FPR and FNR - Demo.mp4 49.08MB
  51. 3. Evaluation Metrics/8. Confusion tables, FPR and FNR - Demo.srt 9.62KB
  52. 3. Evaluation Metrics/9. Geometric Mean, Dominance, Index of Imbalanced Accuracy.mp4 23.06MB
  53. 3. Evaluation Metrics/9. Geometric Mean, Dominance, Index of Imbalanced Accuracy.srt 5.24KB
  54. 4. Udersampling/1. Under-Sampling Methods - Introduction.mp4 31.45MB
  55. 4. Udersampling/1. Under-Sampling Methods - Introduction.srt 6.58KB
  56. 4. Udersampling/10. Edited Nearest Neighbours - Intro.mp4 22.57MB
  57. 4. Udersampling/10. Edited Nearest Neighbours - Intro.srt 5.39KB
  58. 4. Udersampling/11. Edited Nearest Neighbours - Demo.mp4 30.82MB
  59. 4. Udersampling/11. Edited Nearest Neighbours - Demo.srt 5.15KB
  60. 4. Udersampling/12. Repeated Edited Nearest Neighbours - Intro.mp4 24.27MB
  61. 4. Udersampling/12. Repeated Edited Nearest Neighbours - Intro.srt 5.42KB
  62. 4. Udersampling/13. Repeated Edited Nearest Neighbours - Demo.mp4 22.89MB
  63. 4. Udersampling/13. Repeated Edited Nearest Neighbours - Demo.srt 3.90KB
  64. 4. Udersampling/14. All KNN - Intro.mp4 16.27MB
  65. 4. Udersampling/14. All KNN - Intro.srt 4.31KB
  66. 4. Udersampling/15. All KNN - Demo.mp4 22.65MB
  67. 4. Udersampling/15. All KNN - Demo.srt 3.56KB
  68. 4. Udersampling/16. Neighbourhood Cleaning Rule - Intro.mp4 23.04MB
  69. 4. Udersampling/16. Neighbourhood Cleaning Rule - Intro.srt 5.03KB
  70. 4. Udersampling/17. Neighbourhood Cleaning Rule - Demo.mp4 15.90MB
  71. 4. Udersampling/17. Neighbourhood Cleaning Rule - Demo.srt 2.64KB
  72. 4. Udersampling/18. NearMiss - Intro.mp4 17.18MB
  73. 4. Udersampling/18. NearMiss - Intro.srt 4.39KB
  74. 4. Udersampling/19. NearMiss - Demo.mp4 26.33MB
  75. 4. Udersampling/19. NearMiss - Demo.srt 4.54KB
  76. 4. Udersampling/2. Random Under-Sampling - Intro.mp4 25.62MB
  77. 4. Udersampling/2. Random Under-Sampling - Intro.srt 6.60KB
  78. 4. Udersampling/20. Instance Hardness Threshold - Intro.mp4 19.70MB
  79. 4. Udersampling/20. Instance Hardness Threshold - Intro.srt 4.95KB
  80. 4. Udersampling/21. Instance Hardness Threshold - Demo.mp4 30.54MB
  81. 4. Udersampling/21. Instance Hardness Threshold - Demo.srt 4.85KB
  82. 4. Udersampling/22. Undersampling Method Comparison.mp4 47.52MB
  83. 4. Udersampling/22. Undersampling Method Comparison.srt 9.29KB
  84. 4. Udersampling/23. Summary Table.html 140B
  85. 4. Udersampling/23.1 Undersampling-Comparison.pdf 205.54KB
  86. 4. Udersampling/3. Random Under-Sampling - Demo.mp4 66.91MB
  87. 4. Udersampling/3. Random Under-Sampling - Demo.srt 13.47KB
  88. 4. Udersampling/4. Condensed Nearest Neighbours - Intro.mp4 32.43MB
  89. 4. Udersampling/4. Condensed Nearest Neighbours - Intro.srt 8.32KB
  90. 4. Udersampling/5. Condensed Nearest Neighbours - Demo.mp4 52.71MB
  91. 4. Udersampling/5. Condensed Nearest Neighbours - Demo.srt 9.16KB
  92. 4. Udersampling/6. Tomek Links - Intro.mp4 18.97MB
  93. 4. Udersampling/6. Tomek Links - Intro.srt 5.30KB
  94. 4. Udersampling/7. Tomek Links - Demo.mp4 23.98MB
  95. 4. Udersampling/7. Tomek Links - Demo.srt 4.14KB
  96. 4. Udersampling/8. One Sided Selection - Intro.mp4 11.90MB
  97. 4. Udersampling/8. One Sided Selection - Intro.srt 2.79KB
  98. 4. Udersampling/9. One Sided Selection - Demo.mp4 25.59MB
  99. 4. Udersampling/9. One Sided Selection - Demo.srt 4.67KB
  100. 5. Oversampling/1. Over-Sampling Methods - Introduction.mp4 21.09MB
  101. 5. Oversampling/1. Over-Sampling Methods - Introduction.srt 4.36KB
  102. 5. Oversampling/10. Borderline SMOTE.mp4 46.20MB
  103. 5. Oversampling/10. Borderline SMOTE.srt 9.30KB
  104. 5. Oversampling/11. Borderline SMOTE - Demo.mp4 24.77MB
  105. 5. Oversampling/11. Borderline SMOTE - Demo.srt 3.59KB
  106. 5. Oversampling/12. SVM SMOTE.mp4 25.27MB
  107. 5. Oversampling/12. SVM SMOTE.srt 6.06KB
  108. 5. Oversampling/13. SVM SMOTE - Demo.mp4 37.01MB
  109. 5. Oversampling/13. SVM SMOTE - Demo.srt 4.86KB
  110. 5. Oversampling/14. K-Means SMOTE.mp4 27.60MB
  111. 5. Oversampling/14. K-Means SMOTE.srt 6.02KB
  112. 5. Oversampling/15. K-Means SMOTE - Demo.mp4 24.77MB
  113. 5. Oversampling/15. K-Means SMOTE - Demo.srt 3.90KB
  114. 5. Oversampling/16. Over-Sampling Method Comparison.mp4 39.77MB
  115. 5. Oversampling/16. Over-Sampling Method Comparison.srt 7.17KB
  116. 5. Oversampling/2. Random Over-Sampling.mp4 15.65MB
  117. 5. Oversampling/2. Random Over-Sampling.srt 3.70KB
  118. 5. Oversampling/3. Random Over-Sampling - Demo.mp4 35.20MB
  119. 5. Oversampling/3. Random Over-Sampling - Demo.srt 6.32KB
  120. 5. Oversampling/4. SMOTE.mp4 44.61MB
  121. 5. Oversampling/4. SMOTE.srt 10.02KB
  122. 5. Oversampling/5. SMOTE - Demo.mp4 18.38MB
  123. 5. Oversampling/5. SMOTE - Demo.srt 3.17KB
  124. 5. Oversampling/6. SMOTE-NC.mp4 48.03MB
  125. 5. Oversampling/6. SMOTE-NC.srt 10.39KB
  126. 5. Oversampling/7. SMOTE-NC - Demo.mp4 21.43MB
  127. 5. Oversampling/7. SMOTE-NC - Demo.srt 3.33KB
  128. 5. Oversampling/8. ADASYN.mp4 31.60MB
  129. 5. Oversampling/8. ADASYN.srt 7.71KB
  130. 5. Oversampling/9. ADASYN - Demo.mp4 20.95MB
  131. 5. Oversampling/9. ADASYN - Demo.srt 3.74KB
  132. 6. Over and Undersampling/1. Combining Over and Under-sampling - Intro.mp4 36.90MB
  133. 6. Over and Undersampling/1. Combining Over and Under-sampling - Intro.srt 7.26KB
  134. 6. Over and Undersampling/2. Combining Over and Under-sampling - Demo.mp4 34.33MB
  135. 6. Over and Undersampling/2. Combining Over and Under-sampling - Demo.srt 6.30KB
  136. 6. Over and Undersampling/3. Comparison of Over and Under-sampling Methods.mp4 36.54MB
  137. 6. Over and Undersampling/3. Comparison of Over and Under-sampling Methods.srt 6.54KB
  138. 7. Ensemble Methods/1. Ensemble methods with Imbalanced Data.mp4 26.54MB
  139. 7. Ensemble Methods/1. Ensemble methods with Imbalanced Data.srt 5.42KB
  140. 7. Ensemble Methods/2. Foundations of Ensemble Learning.mp4 19.71MB
  141. 7. Ensemble Methods/2. Foundations of Ensemble Learning.srt 3.19KB
  142. 7. Ensemble Methods/3. Bagging.mp4 18.19MB
  143. 7. Ensemble Methods/3. Bagging.srt 3.20KB
  144. 7. Ensemble Methods/4. Bagging plus Over- or Under-Sampling.mp4 42.87MB
  145. 7. Ensemble Methods/4. Bagging plus Over- or Under-Sampling.srt 6.37KB
  146. 7. Ensemble Methods/5. Boosting.mp4 70.58MB
  147. 7. Ensemble Methods/5. Boosting.srt 10.62KB
  148. 7. Ensemble Methods/6. Boosting plus Re-Sampling.mp4 47.31MB
  149. 7. Ensemble Methods/6. Boosting plus Re-Sampling.srt 7.99KB
  150. 7. Ensemble Methods/7. Hybdrid Methods.mp4 30.49MB
  151. 7. Ensemble Methods/7. Hybdrid Methods.srt 5.31KB
  152. 7. Ensemble Methods/8. Ensemble Methods - Demo.mp4 70.85MB
  153. 7. Ensemble Methods/8. Ensemble Methods - Demo.srt 11.80KB
  154. 7. Ensemble Methods/9. Additional Reading Resources.html 1.98KB
  155. 8. Cost Sensitive Learning/1. Cost-sensitive Learning - Intro.mp4 32.73MB
  156. 8. Cost Sensitive Learning/1. Cost-sensitive Learning - Intro.srt 7.79KB
  157. 8. Cost Sensitive Learning/10. MetaCost.mp4 42.57MB
  158. 8. Cost Sensitive Learning/10. MetaCost.srt 8.52KB
  159. 8. Cost Sensitive Learning/11. MetaCost - Demo.mp4 22.94MB
  160. 8. Cost Sensitive Learning/11. MetaCost - Demo.srt 4.47KB
  161. 8. Cost Sensitive Learning/12. Optional MetaCost Base Code.mp4 36.92MB
  162. 8. Cost Sensitive Learning/12. Optional MetaCost Base Code.srt 7.46KB
  163. 8. Cost Sensitive Learning/13. Additional Reading Resources.html 1.97KB
  164. 8. Cost Sensitive Learning/2. Types of Cost.mp4 43.99MB
  165. 8. Cost Sensitive Learning/2. Types of Cost.srt 12.06KB
  166. 8. Cost Sensitive Learning/3. Obtaining the Cost.mp4 18.96MB
  167. 8. Cost Sensitive Learning/3. Obtaining the Cost.srt 4.55KB
  168. 8. Cost Sensitive Learning/4. Cost Sensitive Approaches.mp4 10.33MB
  169. 8. Cost Sensitive Learning/4. Cost Sensitive Approaches.srt 1.83KB
  170. 8. Cost Sensitive Learning/5. Misclassification Cost in Logistic Regression.mp4 18.69MB
  171. 8. Cost Sensitive Learning/5. Misclassification Cost in Logistic Regression.srt 3.63KB
  172. 8. Cost Sensitive Learning/6. Misclassification Cost in Decision Trees.mp4 21.26MB
  173. 8. Cost Sensitive Learning/6. Misclassification Cost in Decision Trees.srt 4.14KB
  174. 8. Cost Sensitive Learning/7. Cost Sensitive Learning with Scikit-learn- Demo.mp4 56.06MB
  175. 8. Cost Sensitive Learning/7. Cost Sensitive Learning with Scikit-learn- Demo.srt 9.01KB
  176. 8. Cost Sensitive Learning/8. Find Optimal Cost with hyperparameter tuning.mp4 22.90MB
  177. 8. Cost Sensitive Learning/8. Find Optimal Cost with hyperparameter tuning.srt 4.38KB
  178. 8. Cost Sensitive Learning/9. Bayes Conditional Risk.mp4 72.04MB
  179. 8. Cost Sensitive Learning/9. Bayes Conditional Risk.srt 14.69KB
  180. 9. Probability Calibration/1. Probability Calibration.mp4 34.09MB
  181. 9. Probability Calibration/1. Probability Calibration.srt 7.29KB
  182. 9. Probability Calibration/10. Calibrating a Classifier with Cost-sensitive Learning.mp4 25.19MB
  183. 9. Probability Calibration/10. Calibrating a Classifier with Cost-sensitive Learning.srt 4.58KB
  184. 9. Probability Calibration/11. Probability Additional reading resources.html 931B
  185. 9. Probability Calibration/2. Probability Calibration Curves.mp4 28.76MB
  186. 9. Probability Calibration/2. Probability Calibration Curves.srt 6.66KB
  187. 9. Probability Calibration/3. Probability Calibration Curves - Demo.mp4 64.88MB
  188. 9. Probability Calibration/3. Probability Calibration Curves - Demo.srt 11.50KB
  189. 9. Probability Calibration/4. Brier Score.mp4 17.15MB
  190. 9. Probability Calibration/4. Brier Score.srt 3.66KB
  191. 9. Probability Calibration/5. Brier Score - Demo.mp4 49.02MB
  192. 9. Probability Calibration/5. Brier Score - Demo.srt 8.83KB
  193. 9. Probability Calibration/6. Under- and Over-sampling and Cost-sensitive learning on Probability Calibration.mp4 29.58MB
  194. 9. Probability Calibration/6. Under- and Over-sampling and Cost-sensitive learning on Probability Calibration.srt 6.24KB
  195. 9. Probability Calibration/7. Calibrating a Classifier.mp4 27.19MB
  196. 9. Probability Calibration/7. Calibrating a Classifier.srt 5.89KB
  197. 9. Probability Calibration/8. Calibrating a Classifier - Demo.mp4 46.73MB
  198. 9. Probability Calibration/8. Calibrating a Classifier - Demo.srt 7.27KB
  199. 9. Probability Calibration/9. Calibrating a Classfiier after SMOTE or Under-sampling.mp4 52.00MB
  200. 9. Probability Calibration/9. Calibrating a Classfiier after SMOTE or Under-sampling.srt 10.38KB