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Machine Learning A-Z - Hands On Python and R In Data Science

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Machine Learning A-Z - Hands On Python and R In Data Science

文件列表
  1. 01 Welcome to the course/004 Installing Python and Anaconda MAC Windows.mp423.96MB
  2. 01 Welcome to the course/003 Installing R and R Studio MAC Windows.mp423.21MB
  3. 01 Welcome to the course/002 Why Machine Learning is the Future.mp414.48MB
  4. 01 Welcome to the course/001 Applications of Machine Learning.mp49.81MB
  5. 02 -------------------------- Part 1 Data Preprocessing --------------------------/012 Categorical Data.mp452.88MB
  6. 02 -------------------------- Part 1 Data Preprocessing --------------------------/013 Splitting the Dataset into the Training set and Test set.mp450.91MB
  7. 02 -------------------------- Part 1 Data Preprocessing --------------------------/014 Feature Scaling.mp444.59MB
  8. 02 -------------------------- Part 1 Data Preprocessing --------------------------/011 Missing Data.mp439.32MB
  9. 02 -------------------------- Part 1 Data Preprocessing --------------------------/009 Importing the Dataset.mp428.64MB
  10. 02 -------------------------- Part 1 Data Preprocessing --------------------------/015 And here is our Data Preprocessing Template.mp425.86MB
  11. 02 -------------------------- Part 1 Data Preprocessing --------------------------/008 Importing the Libraries.mp413.56MB
  12. 02 -------------------------- Part 1 Data Preprocessing --------------------------/007 Get the dataset.mp47.24MB
  13. 02 -------------------------- Part 1 Data Preprocessing --------------------------/006 Welcome to Part 1 - Data Preprocessing.mp43.52MB
  14. 04 Simple Linear Regression/027 Simple Linear Regression in R - Step 4.mp449.16MB
  15. 04 Simple Linear Regression/023 Simple Linear Regression in Python - Step 4.mp439.37MB
  16. 04 Simple Linear Regression/020 Simple Linear Regression in Python - Step 1.mp427.92MB
  17. 04 Simple Linear Regression/025 Simple Linear Regression in R - Step 2.mp424.87MB
  18. 04 Simple Linear Regression/021 Simple Linear Regression in Python - Step 2.mp424.62MB
  19. 04 Simple Linear Regression/022 Simple Linear Regression in Python - Step 3.mp420.55MB
  20. 04 Simple Linear Regression/024 Simple Linear Regression in R - Step 1.mp411.52MB
  21. 04 Simple Linear Regression/026 Simple Linear Regression in R - Step 3.mp411.42MB
  22. 04 Simple Linear Regression/018 Simple Linear Regression Intuition - Step 1.mp410.52MB
  23. 04 Simple Linear Regression/017 Dataset Business Problem Description.mp47.77MB
  24. 04 Simple Linear Regression/019 Simple Linear Regression Intuition - Step 2.mp45.99MB
  25. 05 Multiple Linear Regression/038 Multiple Linear Regression in Python - Backward Elimination - HOMEWORK.mp459.14MB
  26. 05 Multiple Linear Regression/037 Multiple Linear Regression in Python - Backward Elimination - Preparation.mp454.54MB
  27. 05 Multiple Linear Regression/039 Multiple Linear Regression in Python - Backward Elimination - Homework Solution.mp454.26MB
  28. 05 Multiple Linear Regression/034 Multiple Linear Regression in Python - Step 1.mp452.18MB
  29. 05 Multiple Linear Regression/043 Multiple Linear Regression in R - Backward Elimination - HOMEWORK.mp450.78MB
  30. 05 Multiple Linear Regression/041 Multiple Linear Regression in R - Step 2.mp445.22MB
  31. 05 Multiple Linear Regression/033 Multiple Linear Regression Intuition - Step 5.mp432.8MB
  32. 05 Multiple Linear Regression/036 Multiple Linear Regression in Python - Step 3.mp425.48MB
  33. 05 Multiple Linear Regression/040 Multiple Linear Regression in R - Step 1.mp423.44MB
  34. 05 Multiple Linear Regression/044 Multiple Linear Regression in R - Backward Elimination - Homework Solution.mp421.95MB
  35. 05 Multiple Linear Regression/031 Multiple Linear Regression Intuition - Step 3.mp416.59MB
  36. 05 Multiple Linear Regression/042 Multiple Linear Regression in R - Step 3.mp413.85MB
  37. 05 Multiple Linear Regression/028 Dataset Business Problem Description.mp412.56MB
  38. 05 Multiple Linear Regression/035 Multiple Linear Regression in Python - Step 2.mp49.84MB
  39. 05 Multiple Linear Regression/032 Multiple Linear Regression Intuition - Step 4.mp45.34MB
  40. 05 Multiple Linear Regression/030 Multiple Linear Regression Intuition - Step 2.mp42.03MB
  41. 05 Multiple Linear Regression/029 Multiple Linear Regression Intuition - Step 1.mp42MB
  42. 06 Polynomial Regression/053 Polynomial Regression in R - Step 3.mp454.8MB
  43. 06 Polynomial Regression/048 Polynomial Regression in Python - Step 3.mp454.5MB
  44. 06 Polynomial Regression/050 Python Regression Template.mp436.78MB
  45. 06 Polynomial Regression/047 Polynomial Regression in Python - Step 2.mp435.11MB
  46. 06 Polynomial Regression/052 Polynomial Regression in R - Step 2.mp432.28MB
  47. 06 Polynomial Regression/046 Polynomial Regression in Python - Step 1.mp431.64MB
  48. 06 Polynomial Regression/055 R Regression Template.mp431.33MB
  49. 06 Polynomial Regression/054 Polynomial Regression in R - Step 4.mp428.52MB
  50. 06 Polynomial Regression/051 Polynomial Regression in R - Step 1.mp421.21MB
  51. 06 Polynomial Regression/049 Polynomial Regression in Python - Step 4.mp417.65MB
  52. 06 Polynomial Regression/045 Polynomial Regression Intuition.mp49.44MB
  53. 07 Support Vector Regression SVR/056 SVR in Python.mp460.22MB
  54. 07 Support Vector Regression SVR/057 SVR in R.mp433.73MB
  55. 08 Decision Tree Regression/060 Decision Tree Regression in R.mp456.23MB
  56. 08 Decision Tree Regression/059 Decision Tree Regression in Python.mp443.44MB
  57. 08 Decision Tree Regression/058 Decision Tree Regression Intuition.mp425.33MB
  58. 09 Random Forest Regression/062 Random Forest Regression in Python.mp452.69MB
  59. 09 Random Forest Regression/063 Random Forest Regression in R.mp451.86MB
  60. 09 Random Forest Regression/061 Random Forest Regression Intuition.mp415.65MB
  61. 10 Evaluating Regression Models Performance/066 Evaluating Regression Models Performance - Homeworks Final Part.mp428.35MB
  62. 10 Evaluating Regression Models Performance/067 Interpreting Linear Regression Coefficients.mp427.38MB
  63. 10 Evaluating Regression Models Performance/065 Adjusted R-Squared Intuition.mp421.41MB
  64. 10 Evaluating Regression Models Performance/064 R-Squared Intuition.mp49.8MB
  65. 12 Logistic Regression/080 Logistic Regression in R - Step 5.mp493.76MB
  66. 12 Logistic Regression/074 Logistic Regression in Python - Step 5.mp453.15MB
  67. 12 Logistic Regression/069 Logistic Regression Intuition.mp429.17MB
  68. 12 Logistic Regression/078 Logistic Regression in R - Step 3.mp427.44MB
  69. 12 Logistic Regression/075 Python Classification Template.mp417.58MB
  70. 12 Logistic Regression/081 R Classification Template.mp417.5MB
  71. 12 Logistic Regression/070 Logistic Regression in Python - Step 1.mp416.84MB
  72. 12 Logistic Regression/076 Logistic Regression in R - Step 1.mp415.72MB
  73. 12 Logistic Regression/077 Logistic Regression in R - Step 2.mp414.85MB
  74. 12 Logistic Regression/073 Logistic Regression in Python - Step 4.mp413.87MB
  75. 12 Logistic Regression/079 Logistic Regression in R - Step 4.mp411.73MB
  76. 12 Logistic Regression/071 Logistic Regression in Python - Step 2.mp411.1MB
  77. 12 Logistic Regression/072 Logistic Regression in Python - Step 3.mp47.98MB
  78. 13 K-Nearest Neighbors K-NN/084 K-NN in R.mp455.77MB
  79. 13 K-Nearest Neighbors K-NN/083 K-NN in Python.mp446.98MB
  80. 13 K-Nearest Neighbors K-NN/082 K-Nearest Neighbor Intuition.mp410.48MB
  81. 14 Support Vector Machine SVM/087 SVM in R.mp465.31MB
  82. 14 Support Vector Machine SVM/086 SVM in Python.mp441.71MB
  83. 14 Support Vector Machine SVM/085 SVM Intuition.mp419.92MB
  84. 15 Kernel SVM/092 Kernel SVM in Python.mp454.86MB
  85. 15 Kernel SVM/093 Kernel SVM in R.mp452.82MB
  86. 15 Kernel SVM/090 The Kernel Trick.mp434.72MB
  87. 15 Kernel SVM/091 Types of Kernel Functions.mp415.71MB
  88. 15 Kernel SVM/089 Mapping to a higher dimension.mp415.39MB
  89. 15 Kernel SVM/088 Kernel SVM Intuition.mp46.42MB
  90. 16 Naive Bayes/094 Bayes Theorem.mp450.43MB
  91. 16 Naive Bayes/099 Naive Bayes in R.mp449.79MB
  92. 16 Naive Bayes/098 Naive Bayes in Python.mp431.14MB
  93. 16 Naive Bayes/095 Naive Bayes Intuition.mp431.1MB
  94. 16 Naive Bayes/097 Naive Bayes Intuition Extras.mp418.94MB
  95. 16 Naive Bayes/096 Naive Bayes Intuition Challenge Reveal.mp413.27MB
  96. 17 Decision Tree Classification/102 Decision Tree Classification in R.mp468.18MB
  97. 17 Decision Tree Classification/101 Decision Tree Classification in Python.mp438.85MB
  98. 17 Decision Tree Classification/100 Decision Tree Classification Intuition.mp421.63MB
  99. 18 Random Forest Classification/105 Random Forest Classification in R.mp464.11MB
  100. 18 Random Forest Classification/104 Random Forest Classification in Python.mp462.04MB
  101. 18 Random Forest Classification/103 Random Forest Classification Intuition.mp425.66MB
  102. 19 Evaluating Classification Models Performance/109 CAP Curve.mp420.31MB
  103. 19 Evaluating Classification Models Performance/106 False Positives False Negatives.mp415.12MB
  104. 19 Evaluating Classification Models Performance/110 CAP Curve Analysis.mp412.94MB
  105. 19 Evaluating Classification Models Performance/107 Confusion Matrix.mp48.91MB
  106. 19 Evaluating Classification Models Performance/108 Accuracy Paradox.mp44.21MB
  107. 21 K-Means Clustering/115 K-Means Clustering in Python.mp449.81MB
  108. 21 K-Means Clustering/116 K-Means Clustering in R.mp436.91MB
  109. 21 K-Means Clustering/112 K-Means Clustering Intuition.mp429.97MB
  110. 21 K-Means Clustering/114 K-Means Selecting The Number Of Clusters.mp425.68MB
  111. 21 K-Means Clustering/113 K-Means Random Initialization Trap.mp415.36MB
  112. 22 Hierarchical Clustering/119 Hierarchical Clustering Using Dendrograms.mp422.81MB
  113. 22 Hierarchical Clustering/123 HC in Python - Step 4.mp421.32MB
  114. 22 Hierarchical Clustering/118 Hierarchical Clustering How Dendrograms Work.mp417.46MB
  115. 22 Hierarchical Clustering/117 Hierarchical Clustering Intuition.mp416.52MB
  116. 22 Hierarchical Clustering/122 HC in Python - Step 3.mp416.17MB
  117. 22 Hierarchical Clustering/121 HC in Python - Step 2.mp415.51MB
  118. 22 Hierarchical Clustering/126 HC in R - Step 2.mp413.87MB
  119. 22 Hierarchical Clustering/120 HC in Python - Step 1.mp413.77MB
  120. 22 Hierarchical Clustering/129 HC in R - Step 5.mp413.68MB
  121. 22 Hierarchical Clustering/128 HC in R - Step 4.mp410.17MB
  122. 22 Hierarchical Clustering/127 HC in R - Step 3.mp49.95MB
  123. 22 Hierarchical Clustering/124 HC in Python - Step 5.mp49.92MB
  124. 22 Hierarchical Clustering/125 HC in R - Step 1.mp48.59MB
  125. 24 Apriori/133 Apriori in R - Step 3.mp456.51MB
  126. 24 Apriori/131 Apriori in R - Step 1.mp452.83MB
  127. 24 Apriori/134 Apriori in Python - Step 1.mp447.41MB
  128. 24 Apriori/132 Apriori in R - Step 2.mp438.81MB
  129. 24 Apriori/135 Apriori in Python - Step 2.mp437.32MB
  130. 24 Apriori/136 Apriori in Python - Step 3.mp435.3MB
  131. 25 Eclat/137 Eclat in R.mp425.26MB
  132. 27 Upper Confidence Bound UCB/145 Upper Confidence Bound in R - Step 3.mp457.84MB
  133. 27 Upper Confidence Bound UCB/141 Upper Confidence Bound in Python - Step 3.mp453.71MB
  134. 27 Upper Confidence Bound UCB/140 Upper Confidence Bound in Python - Step 2.mp444.49MB
  135. 27 Upper Confidence Bound UCB/139 Upper Confidence Bound in Python - Step 1.mp439.01MB
  136. 27 Upper Confidence Bound UCB/144 Upper Confidence Bound in R - Step 2.mp434.1MB
  137. 27 Upper Confidence Bound UCB/143 Upper Confidence Bound in R - Step 1.mp434.01MB
  138. 27 Upper Confidence Bound UCB/142 Upper Confidence Bound in Python - Step 4.mp412.44MB
  139. 27 Upper Confidence Bound UCB/146 Upper Confidence Bound in R - Step 4.mp49.55MB
  140. 28 Thompson Sampling/147 Thompson Sampling in Python - Step 1.mp455.52MB
  141. 28 Thompson Sampling/149 Thompson Sampling in R - Step 1.mp451.04MB
  142. 28 Thompson Sampling/148 Thompson Sampling in Python - Step 2.mp411.22MB
  143. 28 Thompson Sampling/150 Thompson Sampling in R - Step 2.mp49.56MB
  144. 29 --------------------- Part 7 Natural Language Processing ---------------------/172 Natural Language Processing in R - Step 10.mp454.14MB
  145. 29 --------------------- Part 7 Natural Language Processing ---------------------/159 Natural Language Processing in Python - Step 8.mp452.02MB
  146. 29 --------------------- Part 7 Natural Language Processing ---------------------/163 Natural Language Processing in R - Step 1.mp451.2MB
  147. 29 --------------------- Part 7 Natural Language Processing ---------------------/152 Natural Language Processing in Python - Step 1.mp446.06MB
  148. 29 --------------------- Part 7 Natural Language Processing ---------------------/171 Natural Language Processing in R - Step 9.mp437.69MB
  149. 29 --------------------- Part 7 Natural Language Processing ---------------------/161 Natural Language Processing in Python - Step 10.mp432.91MB
  150. 29 --------------------- Part 7 Natural Language Processing ---------------------/155 Natural Language Processing in Python - Step 4.mp429.75MB
  151. 29 --------------------- Part 7 Natural Language Processing ---------------------/153 Natural Language Processing in Python - Step 2.mp427.44MB
  152. 29 --------------------- Part 7 Natural Language Processing ---------------------/158 Natural Language Processing in Python - Step 7.mp422.13MB
  153. 29 --------------------- Part 7 Natural Language Processing ---------------------/164 Natural Language Processing in R - Step 2.mp421.66MB
  154. 29 --------------------- Part 7 Natural Language Processing ---------------------/160 Natural Language Processing in Python - Step 9.mp418.9MB
  155. 29 --------------------- Part 7 Natural Language Processing ---------------------/156 Natural Language Processing in Python - Step 5.mp418.8MB
  156. 29 --------------------- Part 7 Natural Language Processing ---------------------/170 Natural Language Processing in R - Step 8.mp417.23MB
  157. 29 --------------------- Part 7 Natural Language Processing ---------------------/165 Natural Language Processing in R - Step 3.mp416.89MB
  158. 29 --------------------- Part 7 Natural Language Processing ---------------------/168 Natural Language Processing in R - Step 6.mp416.09MB
  159. 29 --------------------- Part 7 Natural Language Processing ---------------------/169 Natural Language Processing in R - Step 7.mp49.59MB
  160. 29 --------------------- Part 7 Natural Language Processing ---------------------/157 Natural Language Processing in Python - Step 6.mp48.32MB
  161. 29 --------------------- Part 7 Natural Language Processing ---------------------/166 Natural Language Processing in R - Step 4.mp48.24MB
  162. 29 --------------------- Part 7 Natural Language Processing ---------------------/167 Natural Language Processing in R - Step 5.mp45.78MB
  163. 29 --------------------- Part 7 Natural Language Processing ---------------------/154 Natural Language Processing in Python - Step 3.mp44.16MB
  164. 31 Artificial Neural Networks/177 ANN in Python - Step 2.mp484.87MB
  165. 31 Artificial Neural Networks/186 ANN in R - Step 1.mp449.89MB
  166. 31 Artificial Neural Networks/189 ANN in R - Step 4 Last step.mp443.75MB
  167. 31 Artificial Neural Networks/180 ANN in Python - Step 5.mp439.36MB
  168. 31 Artificial Neural Networks/188 ANN in R - Step 3.mp437.85MB
  169. 31 Artificial Neural Networks/176 ANN in Python - Step 1 - Installing Theano Tensorflow and Keras.mp437.45MB
  170. 31 Artificial Neural Networks/183 ANN in Python - Step 8.mp434.03MB
  171. 31 Artificial Neural Networks/175 Business Problem Description.mp429.23MB
  172. 31 Artificial Neural Networks/184 ANN in Python - Step 9.mp428.47MB
  173. 31 Artificial Neural Networks/185 ANN in Python - Step 10.mp428.42MB
  174. 31 Artificial Neural Networks/187 ANN in R - Step 2.mp418.24MB
  175. 31 Artificial Neural Networks/182 ANN in Python - Step 7.mp414.92MB
  176. 31 Artificial Neural Networks/178 ANN in Python - Step 3.mp414.62MB
  177. 31 Artificial Neural Networks/181 ANN in Python - Step 6.mp411.93MB
  178. 31 Artificial Neural Networks/179 ANN in Python - Step 4.mp49.69MB
  179. 32 Convolutional Neural Networks/198 CNN in Python - Step 9.mp462.41MB
  180. 32 Convolutional Neural Networks/193 CNN in Python - Step 4.mp434.62MB
  181. 32 Convolutional Neural Networks/190 CNN in Python - Step 1.mp430.6MB
  182. 32 Convolutional Neural Networks/199 CNN in Python - Step 10.mp427.74MB
  183. 32 Convolutional Neural Networks/196 CNN in Python - Step 7.mp416.65MB
  184. 32 Convolutional Neural Networks/194 CNN in Python - Step 5.mp412.38MB
  185. 32 Convolutional Neural Networks/195 CNN in Python - Step 6.mp411.94MB
  186. 32 Convolutional Neural Networks/197 CNN in Python - Step 8.mp48.95MB
  187. 32 Convolutional Neural Networks/191 CNN in Python - Step 2.mp47.2MB
  188. 32 Convolutional Neural Networks/192 CNN in Python - Step 3.mp42.8MB
  189. 34 Principal Component Analysis PCA/202 PCA in Python - Step 1.mp431.95MB
  190. 34 Principal Component Analysis PCA/204 PCA in Python - Step 3.mp425.51MB
  191. 34 Principal Component Analysis PCA/203 PCA in Python - Step 2.mp422.07MB
  192. 35 Linear Discriminant Analysis LDA/205 LDA in Python.mp445.42MB
  193. 36 Kernel PCA/206 Kernel PCA in Python.mp433.38MB
  194. 38 Model Selection/209 Grid Search in Python - Step 1.mp438.21MB
  195. 38 Model Selection/208 k-Fold Cross Validation in Python.mp432.83MB
  196. 38 Model Selection/210 Grid Search in Python - Step 2.mp429.51MB
  197. 39 XGBoost/212 XGBoost in Python - Step 2.mp431.97MB
  198. 39 XGBoost/211 XGBoost in Python - Step 1.mp421.39MB
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