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GetFreeCourses.Co-Udemy-Machine Learning A-Z™ Python & R in Data Science [2023]

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GetFreeCourses Co-Udemy-Machine Learning A-Z™ Python & R in Data Science 2023

文件列表
  1. 1 - Welcome to the course Here we will help you get started in the best conditions/2 - Machine Learning Demo Get Excited.mp450.77MB
  2. 1 - Welcome to the course Here we will help you get started in the best conditions/4 - How to use the ML AZ folder Google Colab.mp438.04MB
  3. 1 - Welcome to the course Here we will help you get started in the best conditions/5 - Installing R and R Studio Mac Linux Windows.mp452.47MB
  4. 10 - Decision Tree Regression/114 - Decision Tree Regression Intuition.mp429.62MB
  5. 10 - Decision Tree Regression/115 - Decision Tree Regression in Python Step 1a.mp413.63MB
  6. 10 - Decision Tree Regression/116 - Decision Tree Regression in Python Step 1b.mp416.75MB
  7. 10 - Decision Tree Regression/117 - Decision Tree Regression in Python Step 2.mp417.86MB
  8. 10 - Decision Tree Regression/118 - Decision Tree Regression in Python Step 3.mp412.89MB
  9. 10 - Decision Tree Regression/119 - Decision Tree Regression in Python Step 4.mp417.58MB
  10. 10 - Decision Tree Regression/120 - Decision Tree Regression in R Step 1.mp426.83MB
  11. 10 - Decision Tree Regression/121 - Decision Tree Regression in R Step 2.mp464.4MB
  12. 10 - Decision Tree Regression/122 - Decision Tree Regression in R Step 3.mp415.08MB
  13. 10 - Decision Tree Regression/123 - Decision Tree Regression in R Step 4.mp418.26MB
  14. 11 - Random Forest Regression/124 - Random Forest Regression Intuition.mp453.92MB
  15. 11 - Random Forest Regression/125 - Random Forest Regression in Python Step 1.mp426.43MB
  16. 11 - Random Forest Regression/126 - Random Forest Regression in Python Step 2.mp443.8MB
  17. 11 - Random Forest Regression/127 - Random Forest Regression in R Step 1.mp432.93MB
  18. 11 - Random Forest Regression/128 - Random Forest Regression in R Step 2.mp434.74MB
  19. 11 - Random Forest Regression/129 - Random Forest Regression in R Step 3.mp427.04MB
  20. 12 - Evaluating Regression Models Performance/130 - RSquared Intuition.mp416.54MB
  21. 12 - Evaluating Regression Models Performance/131 - Adjusted RSquared Intuition.mp415.71MB
  22. 13 - Regression Model Selection in Python/133 - Preparation of the Regression Code Templates Step 1.mp414.94MB
  23. 13 - Regression Model Selection in Python/134 - Preparation of the Regression Code Templates Step 2.mp433.07MB
  24. 13 - Regression Model Selection in Python/135 - Preparation of the Regression Code Templates Step 3.mp421.7MB
  25. 13 - Regression Model Selection in Python/136 - Preparation of the Regression Code Templates Step 4.mp441.45MB
  26. 13 - Regression Model Selection in Python/137 - THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION STEP 1.mp434.48MB
  27. 13 - Regression Model Selection in Python/138 - THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION STEP 2.mp446.49MB
  28. 14 - Regression Model Selection in R/140 - Evaluating Regression Models Performance Homeworks Final Part.mp446.33MB
  29. 14 - Regression Model Selection in R/141 - Interpreting Linear Regression Coefficients.mp486.86MB
  30. 16 - Logistic Regression/144 - What is Classification.mp47.89MB
  31. 16 - Logistic Regression/145 - Logistic Regression Intuition.mp424.75MB
  32. 16 - Logistic Regression/146 - Maximum Likelihood.mp49.08MB
  33. 16 - Logistic Regression/147 - Logistic Regression in Python Step 1a.mp417.2MB
  34. 16 - Logistic Regression/148 - Logistic Regression in Python Step 1b.mp413.65MB
  35. 16 - Logistic Regression/149 - Logistic Regression in Python Step 2a.mp443.99MB
  36. 16 - Logistic Regression/150 - Logistic Regression in Python Step 2b.mp451.38MB
  37. 16 - Logistic Regression/151 - Logistic Regression in Python Step 3a.mp432.58MB
  38. 16 - Logistic Regression/152 - Logistic Regression in Python Step 3b.mp411.56MB
  39. 16 - Logistic Regression/153 - Logistic Regression in Python Step 4a.mp427MB
  40. 16 - Logistic Regression/154 - Logistic Regression in Python Step 4b.mp46.67MB
  41. 16 - Logistic Regression/155 - Logistic Regression in Python Step 5.mp426.68MB
  42. 16 - Logistic Regression/156 - Logistic Regression in Python Step 6a.mp422.1MB
  43. 16 - Logistic Regression/157 - Logistic Regression in Python Step 6b.mp417.28MB
  44. 16 - Logistic Regression/158 - Logistic Regression in Python Step 7a.mp431.29MB
  45. 16 - Logistic Regression/159 - Logistic Regression in Python Step 7b.mp438.55MB
  46. 16 - Logistic Regression/160 - Logistic Regression in Python Step 7c.mp431.79MB
  47. 16 - Logistic Regression/162 - Logistic Regression in R Step 1.mp432.5MB
  48. 16 - Logistic Regression/163 - Logistic Regression in R Step 2.mp422.75MB
  49. 16 - Logistic Regression/164 - Logistic Regression in R Step 3.mp448.89MB
  50. 16 - Logistic Regression/165 - Logistic Regression in R Step 4.mp450.73MB
  51. 16 - Logistic Regression/167 - Logistic Regression in R Step 5a.mp449.29MB
  52. 16 - Logistic Regression/168 - Logistic Regression in R Step 5b.mp441.58MB
  53. 16 - Logistic Regression/169 - Logistic Regression in R Step 5c.mp465.46MB
  54. 16 - Logistic Regression/171 - R Classification Template.mp440.65MB
  55. 17 - KNearest Neighbors KNN/174 - KNearest Neighbor Intuition.mp413.41MB
  56. 17 - KNearest Neighbors KNN/175 - KNN in Python Step 1.mp457.81MB
  57. 17 - KNearest Neighbors KNN/176 - KNN in Python Step 2.mp452.72MB
  58. 17 - KNearest Neighbors KNN/177 - KNN in Python Step 3.mp453.69MB
  59. 17 - KNearest Neighbors KNN/178 - KNN in R Step 1.mp468.65MB
  60. 17 - KNearest Neighbors KNN/179 - KNN in R Step 2.mp429.85MB
  61. 17 - KNearest Neighbors KNN/180 - KNN in R Step 3.mp462.09MB
  62. 18 - Support Vector Machine SVM/181 - SVM Intuition.mp426.68MB
  63. 18 - Support Vector Machine SVM/182 - SVM in Python Step 1.mp482.86MB
  64. 18 - Support Vector Machine SVM/183 - SVM in Python Step 2.mp456.37MB
  65. 18 - Support Vector Machine SVM/184 - SVM in Python Step 3.mp419.18MB
  66. 18 - Support Vector Machine SVM/185 - SVM in R Step 1.mp483.79MB
  67. 18 - Support Vector Machine SVM/186 - SVM in R Step 2.mp472.55MB
  68. 19 - Kernel SVM/187 - Kernel SVM Intuition.mp49.13MB
  69. 19 - Kernel SVM/188 - Mapping to a higher dimension.mp441.43MB
  70. 19 - Kernel SVM/189 - The Kernel Trick.mp452.69MB
  71. 19 - Kernel SVM/190 - Types of Kernel Functions.mp415.78MB
  72. 19 - Kernel SVM/191 - NonLinear Kernel SVR Advanced.mp445.29MB
  73. 19 - Kernel SVM/192 - Kernel SVM in Python Step 1.mp457.02MB
  74. 19 - Kernel SVM/193 - Kernel SVM in Python Step 2.mp456.5MB
  75. 19 - Kernel SVM/194 - Kernel SVM in R Step 1.mp455.33MB
  76. 19 - Kernel SVM/195 - Kernel SVM in R Step 2.mp430.23MB
  77. 19 - Kernel SVM/196 - Kernel SVM in R Step 3.mp464.44MB
  78. 2 - Part 1 Data Preprocessing/10 - Feature Scaling.mp417.92MB
  79. 2 - Part 1 Data Preprocessing/8 - The Machine Learning process.mp47.98MB
  80. 2 - Part 1 Data Preprocessing/9 - Splitting the data into a Training and Test set.mp47.85MB
  81. 20 - Naive Bayes/197 - Bayes Theorem.mp4195.21MB
  82. 20 - Naive Bayes/198 - Naive Bayes Intuition.mp476.25MB
  83. 20 - Naive Bayes/199 - Naive Bayes Intuition Challenge Reveal.mp418.1MB
  84. 20 - Naive Bayes/200 - Naive Bayes Intuition Extras.mp424.01MB
  85. 20 - Naive Bayes/201 - Naive Bayes in Python Step 1.mp485.62MB
  86. 20 - Naive Bayes/202 - Naive Bayes in Python Step 2.mp464.77MB
  87. 20 - Naive Bayes/203 - Naive Bayes in Python Step 3.mp410.61MB
  88. 20 - Naive Bayes/204 - Naive Bayes in R Step 1.mp430.61MB
  89. 20 - Naive Bayes/205 - Naive Bayes in R Step 2.mp438.83MB
  90. 20 - Naive Bayes/206 - Naive Bayes in R Step 3.mp445.9MB
  91. 21 - Decision Tree Classification/207 - Decision Tree Classification Intuition.mp423.66MB
  92. 21 - Decision Tree Classification/208 - Decision Tree Classification in Python Step 1.mp462.32MB
  93. 21 - Decision Tree Classification/209 - Decision Tree Classification in Python Step 2.mp452.64MB
  94. 21 - Decision Tree Classification/210 - Decision Tree Classification in R Step 1.mp489.87MB
  95. 21 - Decision Tree Classification/211 - Decision Tree Classification in R Step 2.mp471.93MB
  96. 21 - Decision Tree Classification/212 - Decision Tree Classification in R Step 3.mp436MB
  97. 22 - Random Forest Classification/213 - Random Forest Classification Intuition.mp467.99MB
  98. 22 - Random Forest Classification/214 - Random Forest Classification in Python Step 1.mp456.26MB
  99. 22 - Random Forest Classification/215 - Random Forest Classification in Python Step 2.mp452.3MB
  100. 22 - Random Forest Classification/216 - Random Forest Classification in R Step 1.mp438.89MB
  101. 22 - Random Forest Classification/217 - Random Forest Classification in R Step 2.mp462.9MB
  102. 22 - Random Forest Classification/218 - Random Forest Classification in R Step 3.mp476.84MB
  103. 23 - Classification Model Selection in Python/220 - Confusion Matrix Accuracy Ratios.mp428.7MB
  104. 23 - Classification Model Selection in Python/221 - ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION STEP 1.mp431.24MB
  105. 23 - Classification Model Selection in Python/222 - ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION STEP 2.mp451.84MB
  106. 23 - Classification Model Selection in Python/223 - ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION STEP 3.mp433.97MB
  107. 23 - Classification Model Selection in Python/224 - ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION STEP 4.mp412.45MB
  108. 24 - Evaluating Classification Models Performance/225 - False Positives False Negatives.mp426.7MB
  109. 24 - Evaluating Classification Models Performance/226 - Accuracy Paradox.mp45.89MB
  110. 24 - Evaluating Classification Models Performance/227 - CAP Curve.mp425.64MB
  111. 24 - Evaluating Classification Models Performance/228 - CAP Curve Analysis.mp421.1MB
  112. 26 - KMeans Clustering/231 - What is Clustering Supervised vs Unsupervised Learning.mp415.45MB
  113. 26 - KMeans Clustering/232 - KMeans Clustering Intuition.mp44.98MB
  114. 26 - KMeans Clustering/233 - The Elbow Method.mp49.63MB
  115. 26 - KMeans Clustering/234 - KMeans.mp418.73MB
  116. 26 - KMeans Clustering/235 - KMeans Clustering in Python Step 1a.mp415.19MB
  117. 26 - KMeans Clustering/236 - KMeans Clustering in Python Step 1b.mp423.18MB
  118. 26 - KMeans Clustering/237 - KMeans Clustering in Python Step 2a.mp420.07MB
  119. 26 - KMeans Clustering/238 - KMeans Clustering in Python Step 2b.mp419.12MB
  120. 26 - KMeans Clustering/239 - KMeans Clustering in Python Step 3a.mp419.14MB
  121. 26 - KMeans Clustering/240 - KMeans Clustering in Python Step 3b.mp419.53MB
  122. 26 - KMeans Clustering/241 - KMeans Clustering in Python Step 3c.mp414.27MB
  123. 26 - KMeans Clustering/242 - KMeans Clustering in Python Step 4.mp424.55MB
  124. 26 - KMeans Clustering/243 - KMeans Clustering in Python Step 5a.mp422.99MB
  125. 26 - KMeans Clustering/244 - KMeans Clustering in Python Step 5b.mp435.71MB
  126. 26 - KMeans Clustering/245 - KMeans Clustering in Python Step 5c.mp441.33MB
  127. 26 - KMeans Clustering/246 - KMeans Clustering in R Step 1.mp424.02MB
  128. 26 - KMeans Clustering/247 - KMeans Clustering in R Step 2.mp447.13MB
  129. 27 - Hierarchical Clustering/248 - Hierarchical Clustering Intuition.mp436.21MB
  130. 27 - Hierarchical Clustering/249 - Hierarchical Clustering How Dendrograms Work.mp425.9MB
  131. 27 - Hierarchical Clustering/250 - Hierarchical Clustering Using Dendrograms.mp440.92MB
  132. 27 - Hierarchical Clustering/251 - Hierarchical Clustering in Python Step 1.mp431.03MB
  133. 27 - Hierarchical Clustering/252 - Hierarchical Clustering in Python Step 2a.mp416.13MB
  134. 27 - Hierarchical Clustering/253 - Hierarchical Clustering in Python Step 2b.mp436.81MB
  135. 27 - Hierarchical Clustering/254 - Hierarchical Clustering in Python Step 2c.mp447.06MB
  136. 27 - Hierarchical Clustering/255 - Hierarchical Clustering in Python Step 3a.mp425.85MB
  137. 27 - Hierarchical Clustering/256 - Hierarchical Clustering in Python Step 3b.mp423.37MB
  138. 27 - Hierarchical Clustering/257 - Hierarchical Clustering in R Step 1.mp412.22MB
  139. 27 - Hierarchical Clustering/258 - Hierarchical Clustering in R Step 2.mp421.01MB
  140. 27 - Hierarchical Clustering/259 - Hierarchical Clustering in R Step 3.mp449.26MB
  141. 27 - Hierarchical Clustering/260 - Hierarchical Clustering in R Step 4.mp433.96MB
  142. 27 - Hierarchical Clustering/261 - Hierarchical Clustering in R Step 5.mp425.72MB
  143. 29 - Apriori/264 - Apriori Intuition.mp481.56MB
  144. 29 - Apriori/265 - Apriori in Python Step 1.mp4101.7MB
  145. 29 - Apriori/266 - Apriori in Python Step 2.mp4131.63MB
  146. 29 - Apriori/267 - Apriori in Python Step 3.mp458.63MB
  147. 29 - Apriori/268 - Apriori in Python Step 4.mp4192.47MB
  148. 29 - Apriori/269 - Apriori in R Step 1.mp4123.16MB
  149. 29 - Apriori/270 - Apriori in R Step 2.mp4161.94MB
  150. 29 - Apriori/271 - Apriori in R Step 3.mp4269.02MB
  151. 3 - Data Preprocessing in Python/11 - Getting Started Step 1.mp415.28MB
  152. 3 - Data Preprocessing in Python/12 - Getting Started Step 2.mp453.33MB
  153. 3 - Data Preprocessing in Python/13 - Importing the Libraries.mp411.08MB
  154. 3 - Data Preprocessing in Python/14 - Importing the Dataset Step 1.mp418.31MB
  155. 3 - Data Preprocessing in Python/15 - Importing the Dataset Step 2.mp414.36MB
  156. 3 - Data Preprocessing in Python/16 - Importing the Dataset Step 3.mp420.58MB
  157. 3 - Data Preprocessing in Python/18 - Taking care of Missing Data Step 1.mp423.97MB
  158. 3 - Data Preprocessing in Python/19 - Taking care of Missing Data Step 2.mp445.48MB
  159. 3 - Data Preprocessing in Python/20 - Encoding Categorical Data Step 1.mp419.65MB
  160. 3 - Data Preprocessing in Python/21 - Encoding Categorical Data Step 2.mp430.43MB
  161. 3 - Data Preprocessing in Python/22 - Encoding Categorical Data Step 3.mp421.53MB
  162. 3 - Data Preprocessing in Python/23 - Splitting the dataset into the Training set and Test set Step 1.mp415.07MB
  163. 3 - Data Preprocessing in Python/24 - Splitting the dataset into the Training set and Test set Step 2.mp420.51MB
  164. 3 - Data Preprocessing in Python/25 - Splitting the dataset into the Training set and Test set Step 3.mp417.46MB
  165. 3 - Data Preprocessing in Python/26 - Feature Scaling Step 1.mp418.9MB
  166. 3 - Data Preprocessing in Python/27 - Feature Scaling Step 2.mp417.38MB
  167. 3 - Data Preprocessing in Python/28 - Feature Scaling Step 3.mp416.72MB
  168. 3 - Data Preprocessing in Python/29 - Feature Scaling Step 4.mp424.82MB
  169. 30 - Eclat/272 - Eclat Intuition.mp435.29MB
  170. 30 - Eclat/273 - Eclat in Python.mp491.33MB
  171. 30 - Eclat/274 - Eclat in R.mp4110.13MB
  172. 32 - Upper Confidence Bound UCB/276 - The MultiArmed Bandit Problem.mp496.44MB
  173. 32 - Upper Confidence Bound UCB/277 - Upper Confidence Bound UCB Intuition.mp479.23MB
  174. 32 - Upper Confidence Bound UCB/278 - Upper Confidence Bound in Python Step 1.mp466.3MB
  175. 32 - Upper Confidence Bound UCB/279 - Upper Confidence Bound in Python Step 2.mp413.69MB
  176. 32 - Upper Confidence Bound UCB/280 - Upper Confidence Bound in Python Step 3.mp428.59MB
  177. 32 - Upper Confidence Bound UCB/281 - Upper Confidence Bound in Python Step 4.mp463.84MB
  178. 32 - Upper Confidence Bound UCB/282 - Upper Confidence Bound in Python Step 5.mp425.87MB
  179. 32 - Upper Confidence Bound UCB/283 - Upper Confidence Bound in Python Step 6.mp429.76MB
  180. 32 - Upper Confidence Bound UCB/284 - Upper Confidence Bound in Python Step 7.mp431.76MB
  181. 32 - Upper Confidence Bound UCB/285 - Upper Confidence Bound in R Step 1.mp456.62MB
  182. 32 - Upper Confidence Bound UCB/286 - Upper Confidence Bound in R Step 2.mp4121.64MB
  183. 32 - Upper Confidence Bound UCB/287 - Upper Confidence Bound in R Step 3.mp4164.71MB
  184. 32 - Upper Confidence Bound UCB/288 - Upper Confidence Bound in R Step 4.mp413.94MB
  185. 33 - Thompson Sampling/289 - Thompson Sampling Intuition.mp469.13MB
  186. 33 - Thompson Sampling/290 - Algorithm Comparison UCB vs Thompson Sampling.mp423.81MB
  187. 33 - Thompson Sampling/291 - Thompson Sampling in Python Step 1.mp419.49MB
  188. 33 - Thompson Sampling/292 - Thompson Sampling in Python Step 2.mp451.95MB
  189. 33 - Thompson Sampling/293 - Thompson Sampling in Python Step 3.mp462.18MB
  190. 33 - Thompson Sampling/294 - Thompson Sampling in Python Step 4.mp432.27MB
  191. 33 - Thompson Sampling/296 - Thompson Sampling in R Step 1.mp498.77MB
  192. 33 - Thompson Sampling/297 - Thompson Sampling in R Step 2.mp416.42MB
  193. 34 - Part 7 Natural Language Processing/299 - NLP Intuition.mp47.55MB
  194. 34 - Part 7 Natural Language Processing/300 - Types of Natural Language Processing.mp412.13MB
  195. 34 - Part 7 Natural Language Processing/301 - Classical vs Deep Learning Models.mp483.96MB
  196. 34 - Part 7 Natural Language Processing/302 - BagOfWords Model.mp459.37MB
  197. 34 - Part 7 Natural Language Processing/303 - Natural Language Processing in Python Step 1.mp422.43MB
  198. 34 - Part 7 Natural Language Processing/304 - Natural Language Processing in Python Step 2.mp458.33MB
  199. 34 - Part 7 Natural Language Processing/305 - Natural Language Processing in Python Step 3.mp442.5MB
  200. 34 - Part 7 Natural Language Processing/306 - Natural Language Processing in Python Step 4.mp455.18MB
  201. 34 - Part 7 Natural Language Processing/307 - Natural Language Processing in Python Step 5.mp4136.84MB
  202. 34 - Part 7 Natural Language Processing/308 - Natural Language Processing in Python Step 6.mp473.92MB
  203. 34 - Part 7 Natural Language Processing/311 - Natural Language Processing in R Step 1.mp484.05MB
  204. 34 - Part 7 Natural Language Processing/313 - Natural Language Processing in R Step 2.mp440.05MB
  205. 34 - Part 7 Natural Language Processing/314 - Natural Language Processing in R Step 3.mp431.81MB
  206. 34 - Part 7 Natural Language Processing/315 - Natural Language Processing in R Step 4.mp415.02MB
  207. 34 - Part 7 Natural Language Processing/316 - Natural Language Processing in R Step 5.mp410.45MB
  208. 34 - Part 7 Natural Language Processing/317 - Natural Language Processing in R Step 6.mp429.51MB
  209. 34 - Part 7 Natural Language Processing/318 - Natural Language Processing in R Step 7.mp417.78MB
  210. 34 - Part 7 Natural Language Processing/319 - Natural Language Processing in R Step 8.mp428.32MB
  211. 34 - Part 7 Natural Language Processing/320 - Natural Language Processing in R Step 9.mp467.46MB
  212. 34 - Part 7 Natural Language Processing/321 - Natural Language Processing in R Step 10.mp4116.33MB
  213. 35 - Part 8 Deep Learning/324 - What is Deep Learning.mp4178.16MB
  214. 36 - Artificial Neural Networks/325 - Plan of attack.mp46.81MB
  215. 36 - Artificial Neural Networks/326 - The Neuron.mp463.78MB
  216. 36 - Artificial Neural Networks/327 - The Activation Function.mp424.1MB
  217. 36 - Artificial Neural Networks/328 - How do Neural Networks work.mp467.19MB
  218. 36 - Artificial Neural Networks/329 - How do Neural Networks learn.mp466.48MB
  219. 36 - Artificial Neural Networks/330 - Gradient Descent.mp438.28MB
  220. 36 - Artificial Neural Networks/331 - Stochastic Gradient Descent.mp441.59MB
  221. 36 - Artificial Neural Networks/332 - Backpropagation.mp422.89MB
  222. 36 - Artificial Neural Networks/333 - Business Problem Description.mp468.44MB
  223. 36 - Artificial Neural Networks/334 - ANN in Python Step 1.mp481.06MB
  224. 36 - Artificial Neural Networks/335 - ANN in Python Step 2.mp4134.12MB
  225. 36 - Artificial Neural Networks/336 - ANN in Python Step 3.mp459.13MB
  226. 36 - Artificial Neural Networks/337 - ANN in Python Step 4.mp448.56MB
  227. 36 - Artificial Neural Networks/338 - ANN in Python Step 5.mp4119.72MB
  228. 36 - Artificial Neural Networks/339 - ANN in R Step 1.mp4227.63MB
  229. 36 - Artificial Neural Networks/340 - ANN in R Step 2.mp443.59MB
  230. 36 - Artificial Neural Networks/341 - ANN in R Step 3.mp4202.71MB
  231. 36 - Artificial Neural Networks/342 - ANN in R Step 4 Last step.mp495.96MB
  232. 37 - Convolutional Neural Networks/345 - Plan of attack.mp48.93MB
  233. 37 - Convolutional Neural Networks/346 - What are convolutional neural networks.mp4103.85MB
  234. 37 - Convolutional Neural Networks/347 - Step 1 Convolution Operation.mp491.59MB
  235. 37 - Convolutional Neural Networks/348 - Step 1b ReLU Layer.mp431.05MB
  236. 37 - Convolutional Neural Networks/349 - Step 2 Pooling.mp4139.46MB
  237. 37 - Convolutional Neural Networks/350 - Step 3 Flattening.mp44.24MB
  238. 37 - Convolutional Neural Networks/351 - Step 4 Full Connection.mp498.79MB
  239. 37 - Convolutional Neural Networks/352 - Summary.mp416.6MB
  240. 37 - Convolutional Neural Networks/353 - Softmax CrossEntropy.mp463.77MB
  241. 37 - Convolutional Neural Networks/354 - CNN in Python Step 1.mp450.75MB
  242. 37 - Convolutional Neural Networks/355 - CNN in Python Step 2.mp4174.45MB
  243. 37 - Convolutional Neural Networks/356 - CNN in Python Step 3.mp4101.48MB
  244. 37 - Convolutional Neural Networks/357 - CNN in Python Step 4.mp434.86MB
  245. 37 - Convolutional Neural Networks/358 - CNN in Python Step 5.mp4140.16MB
  246. 37 - Convolutional Neural Networks/359 - CNN in Python FINAL DEMO.mp4186.09MB
  247. 39 - Principal Component Analysis PCA/362 - Principal Component Analysis PCA Intuition.mp435.88MB
  248. 39 - Principal Component Analysis PCA/363 - PCA in Python Step 1.mp4136.4MB
  249. 39 - Principal Component Analysis PCA/364 - PCA in Python Step 2.mp433.24MB
  250. 39 - Principal Component Analysis PCA/365 - PCA in R Step 1.mp4175.79MB
  251. 39 - Principal Component Analysis PCA/366 - PCA in R Step 2.mp482.4MB
  252. 39 - Principal Component Analysis PCA/367 - PCA in R Step 3.mp4114.06MB
  253. 4 - Data Preprocessing in R/30 - Getting Started.mp46.56MB
  254. 4 - Data Preprocessing in R/31 - Dataset Description.mp49.59MB
  255. 4 - Data Preprocessing in R/32 - Importing the Dataset.mp411.28MB
  256. 4 - Data Preprocessing in R/33 - Taking care of Missing Data.mp433.12MB
  257. 4 - Data Preprocessing in R/34 - Encoding Categorical Data.mp463.89MB
  258. 4 - Data Preprocessing in R/35 - Splitting the dataset into the Training set and Test set Step 1.mp426.28MB
  259. 4 - Data Preprocessing in R/36 - Splitting the dataset into the Training set and Test set Step 2.mp432.37MB
  260. 4 - Data Preprocessing in R/37 - Feature Scaling Step 1.mp432.08MB
  261. 4 - Data Preprocessing in R/38 - Feature Scaling Step 2.mp461.1MB
  262. 4 - Data Preprocessing in R/39 - Data Preprocessing Template.mp437.85MB
  263. 40 - Linear Discriminant Analysis LDA/368 - Linear Discriminant Analysis LDA Intuition.mp423.57MB
  264. 40 - Linear Discriminant Analysis LDA/369 - LDA in Python.mp4122.81MB
  265. 40 - Linear Discriminant Analysis LDA/370 - LDA in R.mp4165.27MB
  266. 41 - Kernel PCA/371 - Kernel PCA in Python.mp493.25MB
  267. 41 - Kernel PCA/372 - Kernel PCA in R.mp4399.31MB
  268. 43 - Model Selection/374 - kFold Cross Validation in Python.mp497.77MB
  269. 43 - Model Selection/375 - Grid Search in Python.mp4187.7MB
  270. 43 - Model Selection/376 - kFold Cross Validation in R.mp490.34MB
  271. 43 - Model Selection/377 - Grid Search in R.mp485.88MB
  272. 44 - XGBoost/378 - XGBoost in Python.mp4142.56MB
  273. 44 - XGBoost/380 - XGBoost in R.mp4120.96MB
  274. 46 - Annex Logistic Regression Long Explanation/382 - Logistic Regression Intuition.mp444.95MB
  275. 6 - Simple Linear Regression/41 - Simple Linear Regression Intuition.mp46.66MB
  276. 6 - Simple Linear Regression/42 - Ordinary Least Squares.mp412.73MB
  277. 6 - Simple Linear Regression/43 - Simple Linear Regression in Python Step 1a.mp411.83MB
  278. 6 - Simple Linear Regression/44 - Simple Linear Regression in Python Step 1b.mp421.13MB
  279. 6 - Simple Linear Regression/45 - Simple Linear Regression in Python Step 2a.mp412.24MB
  280. 6 - Simple Linear Regression/46 - Simple Linear Regression in Python Step 2b.mp415.55MB
  281. 6 - Simple Linear Regression/47 - Simple Linear Regression in Python Step 3.mp433.81MB
  282. 6 - Simple Linear Regression/48 - Simple Linear Regression in Python Step 4a.mp426.62MB
  283. 6 - Simple Linear Regression/49 - Simple Linear Regression in Python Step 4b.mp429.27MB
  284. 6 - Simple Linear Regression/51 - Simple Linear Regression in R Step 1.mp418.35MB
  285. 6 - Simple Linear Regression/52 - Simple Linear Regression in R Step 2.mp433.2MB
  286. 6 - Simple Linear Regression/53 - Simple Linear Regression in R Step 3.mp425.89MB
  287. 6 - Simple Linear Regression/54 - Simple Linear Regression in R Step 4a.mp450.05MB
  288. 6 - Simple Linear Regression/55 - Simple Linear Regression in R Step 4b.mp434.29MB
  289. 7 - Multiple Linear Regression/56 - Dataset Business Problem Description.mp423.97MB
  290. 7 - Multiple Linear Regression/57 - Multiple Linear Regression Intuition.mp411.74MB
  291. 7 - Multiple Linear Regression/58 - Assumptions of Linear Regression.mp424.61MB
  292. 7 - Multiple Linear Regression/59 - Multiple Linear Regression Intuition Step 3.mp430.24MB
  293. 7 - Multiple Linear Regression/60 - Multiple Linear Regression Intuition Step 4.mp424.69MB
  294. 7 - Multiple Linear Regression/61 - Understanding the PValue.mp434.07MB
  295. 7 - Multiple Linear Regression/62 - Multiple Linear Regression Intuition Step 5.mp448.16MB
  296. 7 - Multiple Linear Regression/63 - Multiple Linear Regression in Python Step 1a.mp429.36MB
  297. 7 - Multiple Linear Regression/64 - Multiple Linear Regression in Python Step 1b.mp418.44MB
  298. 7 - Multiple Linear Regression/65 - Multiple Linear Regression in Python Step 2a.mp444.26MB
  299. 7 - Multiple Linear Regression/66 - Multiple Linear Regression in Python Step 2b.mp458.98MB
  300. 7 - Multiple Linear Regression/67 - Multiple Linear Regression in Python Step 3a.mp421.62MB
  301. 7 - Multiple Linear Regression/68 - Multiple Linear Regression in Python Step 3b.mp422.98MB
  302. 7 - Multiple Linear Regression/69 - Multiple Linear Regression in Python Step 4a.mp438.97MB
  303. 7 - Multiple Linear Regression/70 - Multiple Linear Regression in Python Step 4b.mp421.79MB
  304. 7 - Multiple Linear Regression/73 - Multiple Linear Regression in R Step 1a.mp417.28MB
  305. 7 - Multiple Linear Regression/74 - Multiple Linear Regression in R Step 1b.mp424.37MB
  306. 7 - Multiple Linear Regression/75 - Multiple Linear Regression in R Step 2a.mp445.62MB
  307. 7 - Multiple Linear Regression/76 - Multiple Linear Regression in R Step 2b.mp429.95MB
  308. 7 - Multiple Linear Regression/77 - Multiple Linear Regression in R Step 3.mp424.66MB
  309. 7 - Multiple Linear Regression/78 - Multiple Linear Regression in R Backward Elimination HOMEWORK.mp4109.92MB
  310. 7 - Multiple Linear Regression/79 - Multiple Linear Regression in R Backward Elimination Homework Solution.mp456.49MB
  311. 8 - Polynomial Regression/100 - R Regression Template Step 2.mp421.06MB
  312. 8 - Polynomial Regression/81 - Polynomial Regression Intuition.mp412.89MB
  313. 8 - Polynomial Regression/82 - Polynomial Regression in Python Step 1a.mp410.51MB
  314. 8 - Polynomial Regression/83 - Polynomial Regression in Python Step 1b.mp429MB
  315. 8 - Polynomial Regression/84 - Polynomial Regression in Python Step 2a.mp425.01MB
  316. 8 - Polynomial Regression/85 - Polynomial Regression in Python Step 2b.mp428.2MB
  317. 8 - Polynomial Regression/86 - Polynomial Regression in Python Step 3a.mp430.7MB
  318. 8 - Polynomial Regression/87 - Polynomial Regression in Python Step 3b.mp427.78MB
  319. 8 - Polynomial Regression/88 - Polynomial Regression in Python Step 4a.mp416.63MB
  320. 8 - Polynomial Regression/89 - Polynomial Regression in Python Step 4b.mp412.95MB
  321. 8 - Polynomial Regression/90 - Polynomial Regression in R Step 1a.mp424.14MB
  322. 8 - Polynomial Regression/91 - Polynomial Regression in R Step 1b.mp421.6MB
  323. 8 - Polynomial Regression/92 - Polynomial Regression in R Step 2a.mp424.64MB
  324. 8 - Polynomial Regression/93 - Polynomial Regression in R Step 2b.mp440.68MB
  325. 8 - Polynomial Regression/94 - Polynomial Regression in R Step 3a.mp434.41MB
  326. 8 - Polynomial Regression/95 - Polynomial Regression in R Step 3b.mp431.36MB
  327. 8 - Polynomial Regression/96 - Polynomial Regression in R Step 3c.mp425.18MB
  328. 8 - Polynomial Regression/97 - Polynomial Regression in R Step 4a.mp424.3MB
  329. 8 - Polynomial Regression/98 - Polynomial Regression in R Step 4b.mp423.09MB
  330. 8 - Polynomial Regression/99 - R Regression Template Step 1.mp433.16MB
  331. 9 - Support Vector Regression SVR/101 - SVR Intuition Updated.mp436.83MB
  332. 9 - Support Vector Regression SVR/102 - Headsup on nonlinear SVR.mp419.76MB
  333. 9 - Support Vector Regression SVR/103 - SVR in Python Step 1a.mp417.48MB
  334. 9 - Support Vector Regression SVR/104 - SVR in Python Step 1b.mp414.06MB
  335. 9 - Support Vector Regression SVR/105 - SVR in Python Step 2a.mp426.35MB
  336. 9 - Support Vector Regression SVR/106 - SVR in Python Step 2b.mp422.68MB
  337. 9 - Support Vector Regression SVR/107 - SVR in Python Step 2c.mp412.87MB
  338. 9 - Support Vector Regression SVR/108 - SVR in Python Step 3.mp442.06MB
  339. 9 - Support Vector Regression SVR/109 - SVR in Python Step 4.mp416.18MB
  340. 9 - Support Vector Regression SVR/110 - SVR in Python Step 5a.mp417.4MB
  341. 9 - Support Vector Regression SVR/111 - SVR in Python Step 5b.mp424.71MB
  342. 9 - Support Vector Regression SVR/112 - SVR in R Step 1.mp428.63MB
  343. 9 - Support Vector Regression SVR/113 - SVR in R Step 2.mp420.77MB
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