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[] [UDEMY] A-Z Machine Learning using Azure Machine Learning (AzureML) [FTU]

  • 收录时间:2019-05-12 20:13:51
  • 文件大小:2GB
  • 下载次数:51
  • 最近下载:2021-01-18 21:50:25
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文件列表

  1. 07. Regression Analysis/3. [Hands On] - Linear Regression model using OLS.mp4 91MB
  2. 12. Text Analytics and Natural Language Processing/5. [Hands On] - Classify Customer Complaints using Text Analytics.mp4 91MB
  3. 12. Text Analytics and Natural Language Processing/4. Feature Hashing.mp4 75MB
  4. 01. Basics of Machine Learning/4. Why Machine Learning is the Future.mp4 69MB
  5. 10. Feature Selection - Select a subset of Variables or features with highest impact/9. [Hands On] - Fisher Based LDA - Experiment.mp4 61MB
  6. 01. Basics of Machine Learning/5. What is Machine Learning.mp4 55MB
  7. 12. Text Analytics and Natural Language Processing/2. Text Pre-Processing.mp4 55MB
  8. 04. Classification/2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.mp4 52MB
  9. 12. Text Analytics and Natural Language Processing/3. Bag Of Words and N-Gram Models for Text features.mp4 50MB
  10. 13. Thank You and Bonus Lecture/1. Way Forward.mp4 49MB
  11. 10. Feature Selection - Select a subset of Variables or features with highest impact/2. Pearson Correlation Coefficient.mp4 47MB
  12. 12. Text Analytics and Natural Language Processing/1. What is Text Analytics or Natural Language Processing.mp4 41MB
  13. 03. Data Processing/5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.mp4 39MB
  14. 11. Recommendation System/5. [Hands On] - Restaurant Recommendation Experiment.mp4 36MB
  15. 03. Data Processing/6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.mp4 36MB
  16. 04. Classification/12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.mp4 35MB
  17. 11. Recommendation System/1. What is a Recommendation System.mp4 35MB
  18. 08. Clustering/2. [Hands On] - Cluster Analysis Experiment 1.mp4 31MB
  19. 04. Classification/4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.mp4 29MB
  20. 07. Regression Analysis/5. Gradient Descent.mp4 28MB
  21. 03. Data Processing/4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.mp4 26MB
  22. 04. Classification/10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.mp4 25MB
  23. 10. Feature Selection - Select a subset of Variables or features with highest impact/8. Fisher Based LDA - Intuition.mp4 24MB
  24. 02. Getting Started with Azure ML/2. What is Azure ML and high level architecture..mp4 23MB
  25. 08. Clustering/1. What is Cluster Analysis.mp4 22MB
  26. 03. Data Processing/2. [Hands On] - Data Input-Output - Convert and Unpack.mp4 22MB
  27. 05. Hyperparameter Tuning/1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.mp4 22MB
  28. 04. Classification/6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.mp4 20MB
  29. 04. Classification/3. Logistic Regression - Understand Parameters and Their Impact.mp4 20MB
  30. 01. Basics of Machine Learning/8. Types of Machine Learning Models - Classification, Regression, Clustering etc.mp4 19MB
  31. 01. Basics of Machine Learning/1. What You Will Learn in This Section.mp4 19MB
  32. 01. Basics of Machine Learning/3. Important Message About Udemy Reviews.mp4 19MB
  33. 03. Data Processing/1. [Hands On] - Data Input-Output - Upload Data.mp4 19MB
  34. 04. Classification/13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.mp4 19MB
  35. 08. Clustering/3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.mp4 18MB
  36. 09. Data Processing - Solving Data Processing Challenges/5. [Hands On] - Outliers Treatment - Clip Values.mp4 18MB
  37. 11. Recommendation System/6. Understanding the Matchbox Recommendation Results.mp4 17MB
  38. 07. Regression Analysis/10. [Hands On] - Decision Tree - Experiment Boosted Decision Tree.mp4 17MB
  39. 06. Deploy Webservice/3. [Hands On] - Use the Web Service - Example of Excel.mp4 17MB
  40. 09. Data Processing - Solving Data Processing Challenges/7. [Hands On] - Clean Missing Data with MICE.mp4 16MB
  41. 09. Data Processing - Solving Data Processing Challenges/9. [Hands On] - SMOTE.mp4 16MB
  42. 11. Recommendation System/2. Data Preparation using Recommender Split.mp4 15MB
  43. 11. Recommendation System/3. What is Matchbox Recommender and Train Matchbox Recommender.mp4 15MB
  44. 04. Classification/7. Decision Tree - What is Decision Tree.mp4 14MB
  45. 09. Data Processing - Solving Data Processing Challenges/8. SMOTE - Create New Synthetic Observations.mp4 14MB
  46. 07. Regression Analysis/1. What is Linear Regression.mp4 14MB
  47. 04. Classification/15. [Hands On] - SVM - Adult Census Income Prediction.mp4 14MB
  48. 04. Classification/5. Logistic Regression - Model Selection and Impact Analysis.mp4 14MB
  49. 01. Basics of Machine Learning/6. Understanding various aspects of data - Type, Variables, Category.mp4 14MB
  50. 02. Getting Started with Azure ML/1. What You Will Learn in This Section.mp4 13MB
  51. 01. Basics of Machine Learning/7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.mp4 13MB
  52. 02. Getting Started with Azure ML/5. Azure ML Experiment Workflow.mp4 13MB
  53. 10. Feature Selection - Select a subset of Variables or features with highest impact/6. [Hands On] - Comparison Experiment for Correlation Coefficients.mp4 13MB
  54. 03. Data Processing/3. [Hands On] - Data Input-Output - Import Data.mp4 13MB
  55. 09. Data Processing - Solving Data Processing Challenges/6. Clean Missing Data with MICE.mp4 13MB
  56. 04. Classification/8. Decision Tree - Ensemble Learning - Bagging and Boosting.mp4 13MB
  57. 07. Regression Analysis/2. Regression Analysis - Common Metrics.mp4 13MB
  58. 07. Regression Analysis/8. Decision Tree - What is Regression Tree.mp4 12MB
  59. 02. Getting Started with Azure ML/4. Azure ML Studio Overview and walk-through.mp4 12MB
  60. 04. Classification/9. Decision Tree - Parameters - Two Class Boosted Decision Tree.mp4 12MB
  61. 09. Data Processing - Solving Data Processing Challenges/2. How to Summarize Data.mp4 12MB
  62. 09. Data Processing - Solving Data Processing Challenges/4. Outliers Treatment - Clip Values.mp4 11MB
  63. 04. Classification/1. Logistic Regression - What is Logistic Regression.mp4 11MB
  64. 02. Getting Started with Azure ML/6. Azure ML Cheat Sheet for Model Selection.mp4 11MB
  65. 11. Recommendation System/4. How to Score the Matchbox Recommender.mp4 11MB
  66. 07. Regression Analysis/7. [Hands On] - Experiment Online Gradient.mp4 11MB
  67. 09. Data Processing - Solving Data Processing Challenges/12. PCA - What is PCA and Curse of Dimensionality.mp4 11MB
  68. 09. Data Processing - Solving Data Processing Challenges/14. Join Data - Join Multiple Datasets based on common keys.mp4 10MB
  69. 07. Regression Analysis/4. [Hands On] - Linear Regression - R Squared.mp4 10MB
  70. 06. Deploy Webservice/2. [Hands On] - Deploy Machine Learning Model As a Web Service.vtt 9MB
  71. 06. Deploy Webservice/2. [Hands On] - Deploy Machine Learning Model As a Web Service.mp4 9MB
  72. 10. Feature Selection - Select a subset of Variables or features with highest impact/3. Chi Square Test of Independence.mp4 8MB
  73. 09. Data Processing - Solving Data Processing Challenges/3. [Hands On] - Summarize Data - Experiment.mp4 8MB
  74. 10. Feature Selection - Select a subset of Variables or features with highest impact/1. Feature Selection - Section Introduction.mp4 8MB
  75. 09. Data Processing - Solving Data Processing Challenges/13. [Hands On] - Principal Component Analysis.mp4 7MB
  76. 04. Classification/14. SVM - What is Support Vector Machine.mp4 7MB
  77. 07. Regression Analysis/6. Linear Regression Online Gradient Descent.mp4 7MB
  78. 10. Feature Selection - Select a subset of Variables or features with highest impact/4. Kendall Correlation Coefficient.mp4 7MB
  79. 10. Feature Selection - Select a subset of Variables or features with highest impact/7. [Hands On] - Filter Based Selection - AzureML Experiment.mp4 6MB
  80. 10. Feature Selection - Select a subset of Variables or features with highest impact/5. Spearman's Rank Correlation.mp4 6MB
  81. 09. Data Processing - Solving Data Processing Challenges/11. [Hands On] - Data Normalization.mp4 6MB
  82. 04. Classification/11. Decision Forest - Parameters Explained.mp4 6MB
  83. 09. Data Processing - Solving Data Processing Challenges/15. [Hands On] - Join Data - Experiment.mp4 6MB
  84. 06. Deploy Webservice/1. Azure ML Webservice - Prepare the experiment for webservice.mp4 6MB
  85. 02. Getting Started with Azure ML/3. Creating a Free Azure ML Account.mp4 5MB
  86. 09. Data Processing - Solving Data Processing Challenges/1. Section Introduction.mp4 5MB
  87. 09. Data Processing - Solving Data Processing Challenges/10. Data Normalization - Scale and Reduce.mp4 5MB
  88. 04. Classification/10.1 Bank Telemarketing.csv.csv 5MB
  89. 07. Regression Analysis/9. Decision Tree - What is Boosted Decision Tree Regression.mp4 4MB
  90. 01. Basics of Machine Learning/2.11 Section 04 - Classification - 002 - Decision Tree.pdf.pdf 3MB
  91. 01. Basics of Machine Learning/2.12 Section 11 - Recommendation System.pdf.pdf 3MB
  92. 01. Basics of Machine Learning/2.9 Section 10 - Feature Selection.pdf.pdf 3MB
  93. 01. Basics of Machine Learning/2.10 Section 09 - Data Processing.pdf.pdf 3MB
  94. 01. Basics of Machine Learning/2.8 Section 07 - Regression.pdf.pdf 3MB
  95. 01. Basics of Machine Learning/2.4 Section 02 - Getting Started with AzureML.pdf.pdf 3MB
  96. 02. Getting Started with Azure ML/6.2 ml_studio_overview_v1.1.pdf.pdf 2MB
  97. 01. Basics of Machine Learning/2.13 Section - Text Analytics.pdf.pdf 2MB
  98. 01. Basics of Machine Learning/2.1 Section 01 - Basics of Machine Learning.pdf.pdf 2MB
  99. 01. Basics of Machine Learning/2.6 Section 08 - Clustering.pdf.pdf 2MB
  100. 01. Basics of Machine Learning/2.3 Section 04 - Classification - 001 - Logistic Regression.pdf.pdf 1MB
  101. 01. Basics of Machine Learning/2.7 Section 05 - Tune Hyperparameter.pdf.pdf 1MB
  102. 01. Basics of Machine Learning/2.5 Section 04 - Classification - 003 - SVM.pdf.pdf 1MB
  103. 01. Basics of Machine Learning/2.14 Section 03 - Data Pre-processing.pdf.pdf 1MB
  104. 01. Basics of Machine Learning/2.2 Section 06 - Deploy Webservice.pdf.pdf 702KB
  105. 02. Getting Started with Azure ML/6.1 microsoft-machine-learning-algorithm-cheat-sheet-v6.pdf.pdf 404KB
  106. 13. Thank You and Bonus Lecture/1.1 Links for datasets.pdf.pdf 261KB
  107. FreeCoursesOnline.Me.html 108KB
  108. FTUForum.com.html 100KB
  109. 10. Feature Selection - Select a subset of Variables or features with highest impact/9.1 Wine-Low-Medium-High.csv.csv 95KB
  110. 03. Data Processing/5.1 Wine Quality Dataset.csv.csv 84KB
  111. 04. Classification/6.1 winequality-red.csv.csv 84KB
  112. 12. Text Analytics and Natural Language Processing/5.1 two-class complaints modified.txt.txt 47KB
  113. 04. Classification/2.1 Loan Approval Prediction.csv.csv 37KB
  114. 09. Data Processing - Solving Data Processing Challenges/7.1 MICE Loan Dataset.csv.csv 37KB
  115. Discuss.FTUForum.com.html 32KB
  116. 04. Classification/4.1 004 - Logistic Regression - Understanding the results.xlsx.xlsx 24KB
  117. 04. Classification/2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.vtt 20KB
  118. 03. Data Processing/5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.vtt 16KB
  119. 11. Recommendation System/1. What is a Recommendation System.vtt 15KB
  120. 03. Data Processing/6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.vtt 15KB
  121. 12. Text Analytics and Natural Language Processing/2. Text Pre-Processing.vtt 13KB
  122. 12. Text Analytics and Natural Language Processing/4. Feature Hashing.vtt 13KB
  123. 04. Classification/12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.vtt 13KB
  124. 08. Clustering/2. [Hands On] - Cluster Analysis Experiment 1.vtt 12KB
  125. 04. Classification/4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.vtt 12KB
  126. 11. Recommendation System/5. [Hands On] - Restaurant Recommendation Experiment.vtt 11KB
  127. 04. Classification/3. Logistic Regression - Understand Parameters and Their Impact.vtt 11KB
  128. 03. Data Processing/4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.vtt 10KB
  129. 08. Clustering/1. What is Cluster Analysis.vtt 10KB
  130. 01. Basics of Machine Learning/5. What is Machine Learning.vtt 10KB
  131. 07. Regression Analysis/3. [Hands On] - Linear Regression model using OLS.vtt 10KB
  132. 12. Text Analytics and Natural Language Processing/5. [Hands On] - Classify Customer Complaints using Text Analytics.vtt 10KB
  133. 01. Basics of Machine Learning/4. Why Machine Learning is the Future.vtt 9KB
  134. 01. Basics of Machine Learning/8. Types of Machine Learning Models - Classification, Regression, Clustering etc.vtt 9KB
  135. 07. Regression Analysis/5. Gradient Descent.vtt 9KB
  136. 04. Classification/10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.vtt 9KB
  137. 05. Hyperparameter Tuning/1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.vtt 9KB
  138. 03. Data Processing/2. [Hands On] - Data Input-Output - Convert and Unpack.vtt 8KB
  139. 12. Text Analytics and Natural Language Processing/3. Bag Of Words and N-Gram Models for Text features.vtt 8KB
  140. 04. Classification/6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.vtt 8KB
  141. 01. Basics of Machine Learning/7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.vtt 7KB
  142. 12. Text Analytics and Natural Language Processing/1. What is Text Analytics or Natural Language Processing.vtt 7KB
  143. 11. Recommendation System/2. Data Preparation using Recommender Split.vtt 7KB
  144. 09. Data Processing - Solving Data Processing Challenges/8. SMOTE - Create New Synthetic Observations.vtt 7KB
  145. 11. Recommendation System/3. What is Matchbox Recommender and Train Matchbox Recommender.vtt 7KB
  146. 11. Recommendation System/6. Understanding the Matchbox Recommendation Results.vtt 7KB
  147. 03. Data Processing/1. [Hands On] - Data Input-Output - Upload Data.vtt 7KB
  148. 01. Basics of Machine Learning/6. Understanding various aspects of data - Type, Variables, Category.vtt 7KB
  149. 10. Feature Selection - Select a subset of Variables or features with highest impact/6. [Hands On] - Comparison Experiment for Correlation Coefficients.vtt 7KB
  150. 04. Classification/13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.vtt 7KB
  151. 04. Classification/7. Decision Tree - What is Decision Tree.vtt 7KB
  152. 02. Getting Started with Azure ML/5. Azure ML Experiment Workflow.vtt 7KB
  153. 08. Clustering/3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.vtt 7KB
  154. 10. Feature Selection - Select a subset of Variables or features with highest impact/2. Pearson Correlation Coefficient.vtt 7KB
  155. 04. Classification/8. Decision Tree - Ensemble Learning - Bagging and Boosting.vtt 7KB
  156. 09. Data Processing - Solving Data Processing Challenges/5. [Hands On] - Outliers Treatment - Clip Values.vtt 6KB
  157. 10. Feature Selection - Select a subset of Variables or features with highest impact/1. Feature Selection - Section Introduction.vtt 6KB
  158. 09. Data Processing - Solving Data Processing Challenges/9.1 LoanSMOTE.csv.csv 6KB
  159. 09. Data Processing - Solving Data Processing Challenges/7. [Hands On] - Clean Missing Data with MICE.vtt 6KB
  160. 09. Data Processing - Solving Data Processing Challenges/6. Clean Missing Data with MICE.vtt 6KB
  161. 06. Deploy Webservice/3. [Hands On] - Use the Web Service - Example of Excel.vtt 6KB
  162. 09. Data Processing - Solving Data Processing Challenges/4. Outliers Treatment - Clip Values.vtt 6KB
  163. 02. Getting Started with Azure ML/6. Azure ML Cheat Sheet for Model Selection.vtt 6KB
  164. 04. Classification/1. Logistic Regression - What is Logistic Regression.vtt 6KB
  165. 10. Feature Selection - Select a subset of Variables or features with highest impact/9. [Hands On] - Fisher Based LDA - Experiment.vtt 6KB
  166. 03. Data Processing/3. [Hands On] - Data Input-Output - Import Data.vtt 6KB
  167. 07. Regression Analysis/10. [Hands On] - Decision Tree - Experiment Boosted Decision Tree.vtt 6KB
  168. 09. Data Processing - Solving Data Processing Challenges/2. How to Summarize Data.vtt 6KB
  169. 07. Regression Analysis/2. Regression Analysis - Common Metrics.vtt 6KB
  170. 09. Data Processing - Solving Data Processing Challenges/12. PCA - What is PCA and Curse of Dimensionality.vtt 6KB
  171. 07. Regression Analysis/8. Decision Tree - What is Regression Tree.vtt 5KB
  172. 09. Data Processing - Solving Data Processing Challenges/14. Join Data - Join Multiple Datasets based on common keys.vtt 5KB
  173. 10. Feature Selection - Select a subset of Variables or features with highest impact/3. Chi Square Test of Independence.vtt 5KB
  174. 04. Classification/9. Decision Tree - Parameters - Two Class Boosted Decision Tree.vtt 5KB
  175. 07. Regression Analysis/1. What is Linear Regression.vtt 5KB
  176. 11. Recommendation System/4. How to Score the Matchbox Recommender.vtt 5KB
  177. 04. Classification/5. Logistic Regression - Model Selection and Impact Analysis.vtt 5KB
  178. 09. Data Processing - Solving Data Processing Challenges/9. [Hands On] - SMOTE.vtt 5KB
  179. 10. Feature Selection - Select a subset of Variables or features with highest impact/8. Fisher Based LDA - Intuition.vtt 5KB
  180. 04. Classification/15. [Hands On] - SVM - Adult Census Income Prediction.vtt 5KB
  181. 13. Thank You and Bonus Lecture/1. Way Forward.vtt 5KB
  182. 02. Getting Started with Azure ML/4. Azure ML Studio Overview and walk-through.vtt 5KB
  183. 10. Feature Selection - Select a subset of Variables or features with highest impact/4. Kendall Correlation Coefficient.vtt 4KB
  184. 07. Regression Analysis/7. [Hands On] - Experiment Online Gradient.vtt 4KB
  185. 07. Regression Analysis/4. [Hands On] - Linear Regression - R Squared.vtt 4KB
  186. 01. Basics of Machine Learning/3. Important Message About Udemy Reviews.vtt 4KB
  187. 10. Feature Selection - Select a subset of Variables or features with highest impact/5. Spearman's Rank Correlation.vtt 4KB
  188. 04. Classification/14. SVM - What is Support Vector Machine.vtt 4KB
  189. 10. Feature Selection - Select a subset of Variables or features with highest impact/7. [Hands On] - Filter Based Selection - AzureML Experiment.vtt 4KB
  190. 02. Getting Started with Azure ML/2. What is Azure ML and high level architecture..vtt 3KB
  191. 04. Classification/11. Decision Forest - Parameters Explained.vtt 3KB
  192. 09. Data Processing - Solving Data Processing Challenges/13. [Hands On] - Principal Component Analysis.vtt 3KB
  193. 09. Data Processing - Solving Data Processing Challenges/3. [Hands On] - Summarize Data - Experiment.vtt 3KB
  194. 09. Data Processing - Solving Data Processing Challenges/1. Section Introduction.vtt 3KB
  195. 09. Data Processing - Solving Data Processing Challenges/10. Data Normalization - Scale and Reduce.vtt 3KB
  196. 09. Data Processing - Solving Data Processing Challenges/15. [Hands On] - Join Data - Experiment.vtt 2KB
  197. 01. Basics of Machine Learning/1. What You Will Learn in This Section.vtt 2KB
  198. 06. Deploy Webservice/1. Azure ML Webservice - Prepare the experiment for webservice.vtt 2KB
  199. 02. Getting Started with Azure ML/3. Creating a Free Azure ML Account.vtt 2KB
  200. 09. Data Processing - Solving Data Processing Challenges/11. [Hands On] - Data Normalization.vtt 2KB
  201. 02. Getting Started with Azure ML/1. What You Will Learn in This Section.vtt 2KB
  202. 07. Regression Analysis/6. Linear Regression Online Gradient Descent.vtt 2KB
  203. 03. Data Processing/1.1 Employee Dataset - Full.csv.csv 2KB
  204. 03. Data Processing/4.5 Employee Dataset - TSV.txt.txt 2KB
  205. 07. Regression Analysis/9. Decision Tree - What is Boosted Decision Tree Regression.vtt 2KB
  206. 03. Data Processing/4.1 Employee Dataset - AC1.csv.csv 2KB
  207. 13. Thank You and Bonus Lecture/2. Bonus Lecture.html 1KB
  208. 03. Data Processing/4.2 Employee Dataset - AR2.csv.csv 1KB
  209. 08. Clustering/2.1 Callcenter Data.csv.csv 831B
  210. 03. Data Processing/2.1 Employee Dataset - Full.zip.zip 773B
  211. 03. Data Processing/4.4 Employee Dataset - AR1.csv.csv 672B
  212. [TGx]Downloaded from torrentgalaxy.org.txt 524B
  213. 01. Basics of Machine Learning/2. The course slides for all sections.html 336B
  214. 03. Data Processing/4.3 Employee Dataset - AC2.csv.csv 260B
  215. How you can help Team-FTU.txt 235B
  216. 03. Data Processing/5.2 SQL Statement - Wine.txt.txt 141B
  217. 06. Deploy Webservice/4. AzureML Web Service.html 137B
  218. 07. Regression Analysis/11. Regression Analysis.html 137B
  219. 08. Clustering/4. Clustering or Cluster Analysis.html 137B
  220. 11. Recommendation System/7. Recommendation System.html 137B
  221. 01. Basics of Machine Learning/9. Basics of Machine Learning.html 136B
  222. 02. Getting Started with Azure ML/7. Getting Started with AzureML.html 136B
  223. 03. Data Processing/7. Data Processing.html 136B
  224. 04. Classification/16. Classification Quiz.html 136B
  225. 05. Hyperparameter Tuning/2. Hyperparameter Tuning.html 136B
  226. 09. Data Processing - Solving Data Processing Challenges/15.1 EmpSalaryJC.csv.csv 110B
  227. 09. Data Processing - Solving Data Processing Challenges/15.2 EmpDeptJC.csv.csv 108B
  228. Torrent Downloaded From GloDls.to.txt 84B
  229. 03. Data Processing/3.1 Adult Dataset URL.txt.txt 74B
  230. 04. Classification/13.1 IRIS Dataset Link.txt.txt 74B