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[] Udemy - The Supervised Machine Learning Course

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文件列表

  1. 6 - Support Vector Machines/58 - Kernels Intuition.mp4 77MB
  2. 6 - Support Vector Machines/64 - Crossvalidation.mp4 76MB
  3. 1 - Introduction/1 - Introduction.mp4 70MB
  4. 5 - Decision Trees and Random Forests/41 - Decision Trees Pros and Cons.mp4 69MB
  5. 3 - Naïve Bayes/10 - The HamorSpam Example.mp4 67MB
  6. 3 - Naïve Bayes/9 - Bayes Theorem.mp4 66MB
  7. 6 - Support Vector Machines/55 - Introduction to Support Vector Machines.mp4 62MB
  8. 5 - Decision Trees and Random Forests/52 - Census Data and Income Preprocessing.mp4 60MB
  9. 6 - Support Vector Machines/56 - Linearly separable classes hard margin problem.mp4 59MB
  10. 4 - KNearest Neighbors/37 - Pros and Cons.mp4 55MB
  11. 5 - Decision Trees and Random Forests/45 - Decision Tree Metrics Intuition Gini Inpurity.mp4 53MB
  12. 7 - Ridge and Lasso Regression/78 - Performing Linear Regression.mp4 53MB
  13. 5 - Decision Trees and Random Forests/51 - Random Forest in Code Glass Dataset.mp4 53MB
  14. 4 - KNearest Neighbors/26 - Random Dataset Classification.mp4 51MB
  15. 6 - Support Vector Machines/57 - Nonlinearly separable classes soft margin problem.mp4 50MB
  16. 5 - Decision Trees and Random Forests/40 - Decision Trees in Machine Learning.mp4 47MB
  17. 4 - KNearest Neighbors/34 - KNN vs Linear Regression A Linear Problem.mp4 47MB
  18. 7 - Ridge and Lasso Regression/72 - Ridge Regression Mechanics.mp4 47MB
  19. 4 - KNearest Neighbors/28 - Random Dataset Decision Regions.mp4 46MB
  20. 7 - Ridge and Lasso Regression/76 - The Hitters Dataset Preprocessing and Preparation.mp4 46MB
  21. 3 - Naïve Bayes/14 - The YouTube Dataset Preprocessing.mp4 44MB
  22. 4 - KNearest Neighbors/33 - Theory with a Practical Example.mp4 44MB
  23. 3 - Naïve Bayes/6 - Motivation.mp4 43MB
  24. 7 - Ridge and Lasso Regression/71 - Ridge Regression Basics.mp4 43MB
  25. 5 - Decision Trees and Random Forests/44 - Practical Example Plotting the Tree.mp4 43MB
  26. 3 - Naïve Bayes/20 - The YouTube Dataset Changing the Priors.mp4 40MB
  27. 5 - Decision Trees and Random Forests/47 - Tree Pruning Dealing with Overfitting.mp4 39MB
  28. 3 - Naïve Bayes/19 - The YouTube Dataset Accuracy Precision Recall and the F1 score.mp4 38MB
  29. 3 - Naïve Bayes/13 - CountVectorizer.mp4 37MB
  30. 7 - Ridge and Lasso Regression/77 - Exploratory Data Analysis.mp4 37MB
  31. 6 - Support Vector Machines/66 - Hyperparameter tuning using GridSearchCV.mp4 35MB
  32. 5 - Decision Trees and Random Forests/38 - What is a Tree in Computer Science.mp4 35MB
  33. 7 - Ridge and Lasso Regression/75 - Lasso Regression vs Ridge Regression.mp4 34MB
  34. 3 - Naïve Bayes/12 - The YouTube Dataset Creating the Data Frame.mp4 34MB
  35. 3 - Naïve Bayes/7 - Bayes Thought Experiment.mp4 34MB
  36. 4 - KNearest Neighbors/35 - KNN vs Linear Regression A Nonlinear Problem.mp4 33MB
  37. 5 - Decision Trees and Random Forests/43 - Practical Example Creating a Decision Tree.mp4 33MB
  38. 4 - KNearest Neighbors/29 - Random Dataset Choosing the Best Kvalue.mp4 33MB
  39. 5 - Decision Trees and Random Forests/48 - Random Forest as Ensemble Learning.mp4 32MB
  40. 5 - Decision Trees and Random Forests/39 - The Concept of Decision Trees.mp4 32MB
  41. 6 - Support Vector Machines/59 - Intro to the practical case.mp4 32MB
  42. 7 - Ridge and Lasso Regression/80 - Performing Ridge Regression with Crossvalidation.mp4 31MB
  43. 7 - Ridge and Lasso Regression/82 - Comparing the Results.mp4 31MB
  44. 7 - Ridge and Lasso Regression/81 - Performing Lasso Regression with Crossvalidation.mp4 31MB
  45. 7 - Ridge and Lasso Regression/79 - Crossvalidation for Choosing a Tuning Parameter.mp4 30MB
  46. 5 - Decision Trees and Random Forests/49 - Bootstrapping.mp4 30MB
  47. 2 - Setting up the Environment/2 - Installing Anaconda.mp4 30MB
  48. 7 - Ridge and Lasso Regression/68 - Regression Analysis Overview.mp4 29MB
  49. 6 - Support Vector Machines/63 - Analyzing the results– Confusion Matrix Precision and Recall.mp4 28MB
  50. 4 - KNearest Neighbors/25 - Random Dataset Visualizing the Dataset.mp4 28MB
  51. 7 - Ridge and Lasso Regression/69 - Overfitting and Multicollinearity.mp4 28MB
  52. 4 - KNearest Neighbors/30 - Random Dataset Grid Search.mp4 28MB
  53. 4 - KNearest Neighbors/23 - Math Prerequisites Distance Metrics.mp4 28MB
  54. 5 - Decision Trees and Random Forests/53 - Training the Decision Tree.mp4 27MB
  55. 5 - Decision Trees and Random Forests/54 - Training the Random Forest.mp4 27MB
  56. 4 - KNearest Neighbors/27 - Random Dataset How to Break a Tie.mp4 27MB
  57. 5 - Decision Trees and Random Forests/46 - Decision Tree Metrics Information Gain.mp4 26MB
  58. 7 - Ridge and Lasso Regression/70 - Introduction to Regularization.mp4 26MB
  59. 5 - Decision Trees and Random Forests/50 - From Bootstrapping to Random Forests.mp4 26MB
  60. 4 - KNearest Neighbors/22 - Motivation.mp4 24MB
  61. 3 - Naïve Bayes/16 - The YouTube Dataset Classification.mp4 24MB
  62. 2 - Setting up the Environment/5 - Installing the relevant packages.mp4 23MB
  63. 5 - Decision Trees and Random Forests/42 - Practical Example The Iris Dataset.mp4 22MB
  64. 7 - Ridge and Lasso Regression/74 - Lasso Regression Basics.mp4 22MB
  65. 7 - Ridge and Lasso Regression/83 - Replacing the Missing Values in the DataFrame.mp4 21MB
  66. 4 - KNearest Neighbors/31 - Random Dataset Model Performance.mp4 21MB
  67. 7 - Ridge and Lasso Regression/73 - Regularization in More Complicated Scenarios.mp4 21MB
  68. 2 - Setting up the Environment/4 - Jupyter Dashboard Part 2.mp4 21MB
  69. 6 - Support Vector Machines/65 - Choosing the kernels and C values for crossvalidation.mp4 19MB
  70. 3 - Naïve Bayes/18 - The YouTube Dataset Confusion Matrix.mp4 18MB
  71. 4 - KNearest Neighbors/24 - Random Dataset Generating the Dataset.mp4 17MB
  72. 6 - Support Vector Machines/61 - Splitting the data into train and test and rescaling.mp4 16MB
  73. 6 - Support Vector Machines/60 - Preprocessing the data.mp4 15MB
  74. 3 - Naïve Bayes/21 - 365-ML-infographic.pdf 14MB
  75. 3 - Naïve Bayes/6 - 365-ML-infographic.pdf 14MB
  76. 4 - KNearest Neighbors/22 - 365-ML-infographic.pdf 14MB
  77. 4 - KNearest Neighbors/37 - 365-ML-infographic.pdf 14MB
  78. 6 - Support Vector Machines/55 - 365-ML-infographic.pdf 14MB
  79. 7 - Ridge and Lasso Regression/68 - 365-ML-infographic.pdf 14MB
  80. 6 - Support Vector Machines/62 - Implementing a linear SVM.mp4 13MB
  81. 2 - Setting up the Environment/3 - Jupyter Dashboard Part 1.mp4 10MB
  82. 5 - Decision Trees and Random Forests/38 - Course-Notes-Decision-Trees-and-Random-Forests.pdf 1006KB
  83. 5 - Decision Trees and Random Forests/54 - Course-Notes-Decision-Trees-and-Random-Forests.pdf 1006KB
  84. 5 - Decision Trees and Random Forests/52 - Census-Income-Dataset.zip 612KB
  85. 3 - Naïve Bayes/21 - Machine-Learning-with-Naive-Bayes-Course-Notes-365-Data-Science.pdf 519KB
  86. 3 - Naïve Bayes/6 - Machine-Learning-with-Naive-Bayes-Course-Notes-365-Data-Science.pdf 519KB
  87. 4 - KNearest Neighbors/22 - Machine-Learning-with-K-Nearest-Neighbors-Course-Notes-365-Data-Science.pdf 448KB
  88. 4 - KNearest Neighbors/37 - Machine-Learning-with-K-Nearest-Neighbors-Course-Notes-365-Data-Science.pdf 448KB
  89. 5 - Decision Trees and Random Forests/53 - 5.16.Census-Data-Decision-Tree.ipynb 445KB
  90. 6 - Support Vector Machines/59 - mushrooms-full-dataset.csv 357KB
  91. 6 - Support Vector Machines/67 - Social-Purchase-SVMs-Assignment-3.ipynb 316KB
  92. 6 - Support Vector Machines/67 - Social-Purchase-SVMs-Assignment-3-Solution.ipynb 316KB
  93. 4 - KNearest Neighbors/36 - KNeighborsRegressor-Exercise.zip 291KB
  94. 5 - Decision Trees and Random Forests/44 - 5.7.Full-Iris-code.ipynb 246KB
  95. 3 - Naïve Bayes/12 - Notebooks-and-Dataset.zip 169KB
  96. 3 - Naïve Bayes/15 - youtube-dataset.zip 159KB
  97. 3 - Naïve Bayes/17 - youtube-dataset.zip 159KB
  98. 5 - Decision Trees and Random Forests/54 - 5.17.Census-Data-Random-Forest.ipynb 76KB
  99. 5 - Decision Trees and Random Forests/52 - 5.15.Census-Data-Preprocessing.ipynb 70KB
  100. 7 - Ridge and Lasso Regression/83 - Exercise-Solutions.ipynb 47KB
  101. 6 - Support Vector Machines/65 - 3.8-Support-Vector-Machines-Classification-complete.ipynb 35KB
  102. 7 - Ridge and Lasso Regression/76 - Hitters.csv 20KB
  103. 6 - Support Vector Machines/67 - social.csv 13KB
  104. 5 - Decision Trees and Random Forests/51 - 5.14.Random-Forest-Code-Glass-Dataset.ipynb 13KB
  105. 7 - Ridge and Lasso Regression/76 - Multiple-Linear-Regression-Ridge-Lasso-Hitters.ipynb 12KB
  106. 7 - Ridge and Lasso Regression/76 - Hitters-Data-Legend.xlsx 11KB
  107. 5 - Decision Trees and Random Forests/43 - 5.6.Creating-a-Decision-Tree.ipynb 10KB
  108. 4 - KNearest Neighbors/24 - KNeighborsClassifier-Notebooks.zip 10KB
  109. 3 - Naïve Bayes/17 - Exercise-2.ipynb 8KB
  110. 4 - KNearest Neighbors/32 - KNeighborsClassifier-Exercise.zip 8KB
  111. 3 - Naïve Bayes/17 - Exercise-2-solution.ipynb 8KB
  112. 3 - Naïve Bayes/15 - Exercise-1-solution.ipynb 8KB
  113. 3 - Naïve Bayes/21 - Exercise-3-solution.ipynb 7KB
  114. 3 - Naïve Bayes/15 - Exercise-1.ipynb 7KB
  115. 6 - Support Vector Machines/60 - 3.1-Support-Vector-Machines-Classification-Notebook.ipynb 6KB
  116. 4 - KNearest Neighbors/35 - NonLinearProblem-Notebooks.zip 6KB
  117. 7 - Ridge and Lasso Regression/83 - Exercise.ipynb 6KB
  118. 4 - KNearest Neighbors/34 - LinearProblem-Notebooks.zip 5KB
  119. 4 - KNearest Neighbors/33 - KNeighborsRegressor-Notebooks.zip 5KB
  120. 3 - Naïve Bayes/21 - Exercise-3.ipynb 4KB
  121. 5 - Decision Trees and Random Forests/51 - Glass-dataset.zip 4KB
  122. 6 - Support Vector Machines/67 - Support Vector Machines Assignment.html 509B
  123. 3 - Naïve Bayes/11 - The HamorSpam Example Assignment.html 184B
  124. 0. Websites you may like/[CourseClub.Me].url 122B
  125. 1 - Introduction/[CourseClub.Me].url 122B
  126. 4 - KNearest Neighbors/[CourseClub.Me].url 122B
  127. 7 - Ridge and Lasso Regression/[CourseClub.Me].url 122B
  128. [CourseClub.Me].url 122B
  129. 3 - Naïve Bayes/8 - Bayes Thought Experiment Assignment.html 90B
  130. 3 - Naïve Bayes/15 - The YouTube Dataset Preprocessing Assignment.html 60B
  131. 3 - Naïve Bayes/17 - The YouTube Dataset Classification Assignment.html 60B
  132. 3 - Naïve Bayes/21 - Naïve Bayes Assignment.html 60B
  133. 4 - KNearest Neighbors/32 - KNeighbors Classifier Assignment.html 60B
  134. 4 - KNearest Neighbors/36 - KNeighbors Regressor Assignment.html 60B
  135. 0. Websites you may like/[GigaCourse.Com].url 49B
  136. 1 - Introduction/[GigaCourse.Com].url 49B
  137. 4 - KNearest Neighbors/[GigaCourse.Com].url 49B
  138. 7 - Ridge and Lasso Regression/[GigaCourse.Com].url 49B
  139. [GigaCourse.Com].url 49B
  140. 3 - Naïve Bayes/1 - Bayes Thought Experiment.html 0B
  141. 3 - Naïve Bayes/2 - Bayes Theorem.html 0B
  142. 3 - Naïve Bayes/3 - The HamorSpam Example.html 0B
  143. 4 - KNearest Neighbors/4 - Motivation.html 0B
  144. 4 - KNearest Neighbors/5 - Math Prerequisites Distance Metrics.html 0B
  145. 6 - Support Vector Machines/6 - Intro to SVMs.html 0B
  146. 6 - Support Vector Machines/7 - Hard margin problem.html 0B
  147. 6 - Support Vector Machines/8 - Kernels.html 0B
  148. 6 - Support Vector Machines/9 - Implementing a linear SVM.html 0B
  149. 7 - Ridge and Lasso Regression/10 - Ridge Regression Mechanics.html 0B
  150. 7 - Ridge and Lasso Regression/11 - Lasso Regression Basics.html 0B
  151. 7 - Ridge and Lasso Regression/12 - Crossvalidation for Choosing a Tuning Parameter.html 0B