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[] Udemy - Deep Learning A-Z™ Hands-On Artificial Neural Networks

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文件列表

  1. 1. Welcome to the course/1. Updates on Udemy Reviews.mp4 61MB
  2. 6. Evaluating, Improving and Tuning the ANN/1. Evaluating the ANN.mp4 56MB
  3. 14. RNN Intuition/6. Practical intuition.mp4 53MB
  4. 26. Building an AutoEncoder/16. THANK YOU bonus video.mp4 52MB
  5. 6. Evaluating, Improving and Tuning the ANN/3. Tuning the ANN.mp4 51MB
  6. 26. Building an AutoEncoder/8. Building an AutoEncoder - Step 4.mp4 50MB
  7. 10. Building a CNN/12. Building a CNN - Step 9.mp4 47MB
  8. 14. RNN Intuition/5. LSTMs.mp4 46MB
  9. 4. Building an ANN/6. Building an ANN - Step 2.mp4 46MB
  10. 23. Building a Boltzmann Machine/8. Building a Boltzmann Machine - Step 4.mp4 46MB
  11. 18. SOMs Intuition/8. Reading an Advanced SOM.mp4 43MB
  12. 23. Building a Boltzmann Machine/17. Building a Boltzmann Machine - Step 13.mp4 43MB
  13. 9. CNN Intuition/8. Step 4 - Full Connection.mp4 43MB
  14. 30. Classification Template/5. Logistic Regression Implementation - Step 5.mp4 42MB
  15. 11. Homework - What's that pet/2. Homework Solution.mp4 41MB
  16. 23. Building a Boltzmann Machine/18. Building a Boltzmann Machine - Step 14.mp4 40MB
  17. 9. CNN Intuition/6. Step 2 - Pooling.mp4 40MB
  18. 15. Building a RNN/15. Building a RNN - Step 13.mp4 40MB
  19. 26. Building an AutoEncoder/10. Building an AutoEncoder - Step 6.mp4 38MB
  20. 5. Homework Challenge - Should we say goodbye to that customer/2. Homework Solution.mp4 38MB
  21. 14. RNN Intuition/3. The idea behind Recurrent Neural Networks.mp4 37MB
  22. 15. Building a RNN/6. Building a RNN - Step 4.mp4 37MB
  23. 19. Building a SOM/4. Building a SOM - Step 3.mp4 36MB
  24. 20. Mega Case Study/3. Mega Case Study - Step 3.mp4 35MB
  25. 26. Building an AutoEncoder/12. Building an AutoEncoder - Step 8.mp4 34MB
  26. 26. Building an AutoEncoder/11. Building an AutoEncoder - Step 7.mp4 34MB
  27. 9. CNN Intuition/10. Softmax & Cross-Entropy.mp4 33MB
  28. 22. Boltzmann Machine Intuition/5. Restricted Boltzmann Machine.mp4 32MB
  29. 26. Building an AutoEncoder/13. Building an AutoEncoder - Step 9.mp4 32MB
  30. 1. Welcome to the course/2. What is Deep Learning.mp4 31MB
  31. 9. CNN Intuition/4. Step 1 - Convolution Operation.mp4 31MB
  32. 23. Building a Boltzmann Machine/16. Building a Boltzmann Machine - Step 12.mp4 31MB
  33. 19. Building a SOM/2. Building a SOM - Step 1.mp4 31MB
  34. 4. Building an ANN/9. Building an ANN - Step 5.mp4 30MB
  35. 3. ANN Intuition/2. The Neuron.mp4 30MB
  36. 9. CNN Intuition/3. What are convolutional neural networks.mp4 29MB
  37. 15. Building a RNN/13. Building a RNN - Step 11.mp4 29MB
  38. 23. Building a Boltzmann Machine/12. Building a Boltzmann Machine - Step 8.mp4 29MB
  39. 28. Regression & Classification Intuition/5. Logistic Regression Intuition.mp4 29MB
  40. 14. RNN Intuition/4. The Vanishing Gradient Problem.mp4 29MB
  41. 29. Data Preprocessing Template/4. Data Preprocessing - Step 4.mp4 29MB
  42. 19. Building a SOM/5. Building a SOM - Step 4.mp4 29MB
  43. 26. Building an AutoEncoder/15. Building an AutoEncoder - Step 11.mp4 28MB
  44. 26. Building an AutoEncoder/5. Building an AutoEncoder - Step 2.mp4 28MB
  45. 10. Building a CNN/7. Building a CNN - Step 4.mp4 27MB
  46. 3. ANN Intuition/5. How do Neural Networks learn.mp4 27MB
  47. 15. Building a RNN/7. Building a RNN - Step 5.mp4 26MB
  48. 26. Building an AutoEncoder/4. Building an AutoEncoder - Step 1.mp4 26MB
  49. 18. SOMs Intuition/5. How do Self-Organizing Maps Learn (Part 1).mp4 25MB
  50. 22. Boltzmann Machine Intuition/2. Boltzmann Machine.mp4 25MB
  51. 22. Boltzmann Machine Intuition/6. Contrastive Divergence.mp4 25MB
  52. 23. Building a Boltzmann Machine/14. Building a Boltzmann Machine - Step 10.mp4 24MB
  53. 4. Building an ANN/5. Building an ANN - Step 1.mp4 24MB
  54. 3. ANN Intuition/4. How do Neural Networks work.mp4 24MB
  55. 23. Building a Boltzmann Machine/11. Building a Boltzmann Machine - Step 7.mp4 23MB
  56. 29. Data Preprocessing Template/5. Data Preprocessing - Step 5.mp4 23MB
  57. 29. Data Preprocessing Template/6. Data Preprocessing - Step 6.mp4 23MB
  58. 20. Mega Case Study/4. Mega Case Study - Step 4.mp4 23MB
  59. 29. Data Preprocessing Template/3. Data Preprocessing - Step 3.mp4 22MB
  60. 15. Building a RNN/17. Building a RNN - Step 15.mp4 22MB
  61. 25. AutoEncoders Intuition/2. Auto Encoders.mp4 22MB
  62. 15. Building a RNN/16. Building a RNN - Step 14.mp4 22MB
  63. 18. SOMs Intuition/4. K-Means Clustering (Refresher).mp4 21MB
  64. 23. Building a Boltzmann Machine/5. Building a Boltzmann Machine - Step 1.mp4 21MB
  65. 23. Building a Boltzmann Machine/3. Building a Boltzmann Machine - Introduction.mp4 21MB
  66. 23. Building a Boltzmann Machine/6. Building a Boltzmann Machine - Step 2.mp4 21MB
  67. 15. Building a RNN/9. Building a RNN - Step 7.mp4 21MB
  68. 10. Building a CNN/13. Building a CNN - Step 10.mp4 21MB
  69. 1. Welcome to the course/4. Installing Python.mp4 20MB
  70. 26. Building an AutoEncoder/6. Building an AutoEncoder - Step 3.mp4 20MB
  71. 6. Evaluating, Improving and Tuning the ANN/2. Improving the ANN.mp4 20MB
  72. 19. Building a SOM/3. Building a SOM - Step 2.mp4 19MB
  73. 10. Building a CNN/4. Building a CNN - Step 1.mp4 19MB
  74. 23. Building a Boltzmann Machine/10. Building a Boltzmann Machine - Step 6.mp4 19MB
  75. 3. ANN Intuition/6. Gradient Descent.mp4 19MB
  76. 18. SOMs Intuition/10. EXTRA K-means Clustering (part 3).mp4 18MB
  77. 22. Boltzmann Machine Intuition/4. Editing Wikipedia - Our Contribution to the World.mp4 18MB
  78. 23. Building a Boltzmann Machine/7. Building a Boltzmann Machine - Step 3.mp4 18MB
  79. 4. Building an ANN/12. Building an ANN - Step 8.mp4 18MB
  80. 4. Building an ANN/14. Building an ANN - Step 10.mp4 17MB
  81. 4. Building an ANN/13. Building an ANN - Step 9.mp4 17MB
  82. 3. ANN Intuition/7. Stochastic Gradient Descent.mp4 17MB
  83. 23. Building a Boltzmann Machine/15. Building a Boltzmann Machine - Step 11.mp4 17MB
  84. 4. Building an ANN/3. Business Problem Description.mp4 16MB
  85. 18. SOMs Intuition/2. How do Self-Organizing Maps Work.mp4 16MB
  86. 15. Building a RNN/5. Building a RNN - Step 3.mp4 16MB
  87. 29. Data Preprocessing Template/2. Data Preprocessing - Step 2.mp4 16MB
  88. 22. Boltzmann Machine Intuition/3. Energy-Based Models (EBM).mp4 16MB
  89. 15. Building a RNN/4. Building a RNN - Step 2.mp4 16MB
  90. 18. SOMs Intuition/6. How do Self-Organizing Maps Learn (Part 2).mp4 15MB
  91. 23. Building a Boltzmann Machine/13. Building a Boltzmann Machine - Step 9.mp4 15MB
  92. 3. ANN Intuition/3. The Activation Function.mp4 15MB
  93. 9. CNN Intuition/5. Step 1(b) - ReLU Layer.mp4 14MB
  94. 15. Building a RNN/3. Building a RNN - Step 1.mp4 14MB
  95. 15. Building a RNN/14. Building a RNN - Step 12.mp4 13MB
  96. 15. Building a RNN/10. Building a RNN - Step 8.mp4 13MB
  97. 29. Data Preprocessing Template/1. Data Preprocessing - Step 1.mp4 13MB
  98. 18. SOMs Intuition/7. Live SOM example.mp4 13MB
  99. 10. Building a CNN/10. Building a CNN - Step 7.mp4 13MB
  100. 18. SOMs Intuition/9. EXTRA K-means Clustering (part 2).mp4 12MB
  101. 30. Classification Template/1. Logistic Regression Implementation - Step 1.mp4 12MB
  102. 26. Building an AutoEncoder/9. Building an AutoEncoder - Step 5.mp4 12MB
  103. 30. Classification Template/6. Classification Template.mp4 12MB
  104. 25. AutoEncoders Intuition/6. Sparse Autoencoders.mp4 12MB
  105. 15. Building a RNN/12. Building a RNN - Step 10.mp4 11MB
  106. 26. Building an AutoEncoder/14. Building an AutoEncoder - Step 10.mp4 11MB
  107. 25. AutoEncoders Intuition/4. Training an Auto Encoder.mp4 11MB
  108. 23. Building a Boltzmann Machine/9. Building a Boltzmann Machine - Step 5.mp4 11MB
  109. 3. ANN Intuition/8. Backpropagation.mp4 11MB
  110. 22. Boltzmann Machine Intuition/7. Deep Belief Networks.mp4 10MB
  111. 10. Building a CNN/8. Building a CNN - Step 5.mp4 10MB
  112. 10. Building a CNN/9. Building a CNN - Step 6.mp4 10MB
  113. 30. Classification Template/4. Logistic Regression Implementation - Step 4.mp4 10MB
  114. 20. Mega Case Study/2. Mega Case Study - Step 2.mp4 10MB
  115. 28. Regression & Classification Intuition/2. Simple Linear Regression Intuition - Step 1.mp4 9MB
  116. 4. Building an ANN/11. Building an ANN - Step 7.mp4 9MB
  117. 4. Building an ANN/7. Building an ANN - Step 3.mp4 8MB
  118. 15. Building a RNN/11. Building a RNN - Step 9.mp4 8MB
  119. 30. Classification Template/2. Logistic Regression Implementation - Step 2.mp4 8MB
  120. 29. Data Preprocessing Template/7. Data Preprocessing Template.mp4 8MB
  121. 9. CNN Intuition/9. Summary.mp4 8MB
  122. 10. Building a CNN/3. Introduction to CNNs.mp4 8MB
  123. 14. RNN Intuition/7. EXTRA LSTM Variations.mp4 7MB
  124. 4. Building an ANN/10. Building an ANN - Step 6.mp4 7MB
  125. 10. Building a CNN/11. Building a CNN - Step 8.mp4 7MB
  126. 15. Building a RNN/8. Building a RNN - Step 6.mp4 7MB
  127. 15. Building a RNN/1. How to get the dataset.mp4 7MB
  128. 1. Welcome to the course/5. How to get the dataset.mp4 6MB
  129. 10. Building a CNN/1. How to get the dataset.mp4 6MB
  130. 19. Building a SOM/1. How to get the dataset.mp4 6MB
  131. 23. Building a Boltzmann Machine/1. How to get the dataset.mp4 6MB
  132. 26. Building an AutoEncoder/1. How to get the dataset.mp4 6MB
  133. 4. Building an ANN/2. How to get the dataset.mp4 6MB
  134. 25. AutoEncoders Intuition/5. Overcomplete hidden layers.mp4 6MB
  135. 30. Classification Template/3. Logistic Regression Implementation - Step 3.mp4 6MB
  136. 4. Building an ANN/8. Building an ANN - Step 4.mp4 6MB
  137. 10. Building a CNN/5. Building a CNN - Step 2.mp4 6MB
  138. 28. Regression & Classification Intuition/3. Simple Linear Regression Intuition - Step 2.mp4 5MB
  139. 9. CNN Intuition/2. Plan of attack.mp4 5MB
  140. 22. Boltzmann Machine Intuition/8. Deep Boltzmann Machines.mp4 5MB
  141. 25. AutoEncoders Intuition/7. Denoising Autoencoders.mp4 5MB
  142. 3. ANN Intuition/1. Plan of Attack.mp4 5MB
  143. 18. SOMs Intuition/1. Plan of attack.mp4 4MB
  144. 25. AutoEncoders Intuition/8. Contractive Autoencoders.mp4 4MB
  145. 20. Mega Case Study/1. Mega Case Study - Step 1.mp4 4MB
  146. 14. RNN Intuition/2. Plan of attack.mp4 4MB
  147. 25. AutoEncoders Intuition/9. Stacked Autoencoders.mp4 4MB
  148. 18. SOMs Intuition/3. Why revisit K-Means.mp4 3MB
  149. 25. AutoEncoders Intuition/1. Plan of attack.mp4 3MB
  150. 9. CNN Intuition/7. Step 3 - Flattening.mp4 3MB
  151. 22. Boltzmann Machine Intuition/1. Plan of attack.mp4 3MB
  152. 25. AutoEncoders Intuition/10. Deep Autoencoders.mp4 3MB
  153. 10. Building a CNN/6. Building a CNN - Step 3.mp4 2MB
  154. 25. AutoEncoders Intuition/3. A Note on Biases.mp4 2MB
  155. 28. Regression & Classification Intuition/4. Multiple Linear Regression Intuition.mp4 2MB
  156. 23. Building a Boltzmann Machine/8. Building a Boltzmann Machine - Step 4.srt 42KB
  157. 26. Building an AutoEncoder/8. Building an AutoEncoder - Step 4.srt 41KB
  158. 6. Evaluating, Improving and Tuning the ANN/1. Evaluating the ANN.srt 40KB
  159. 10. Building a CNN/12. Building a CNN - Step 9.srt 40KB
  160. 14. RNN Intuition/5. LSTMs.srt 39KB
  161. 9. CNN Intuition/8. Step 4 - Full Connection.srt 39KB
  162. 22. Boltzmann Machine Intuition/5. Restricted Boltzmann Machine.srt 38KB
  163. 6. Evaluating, Improving and Tuning the ANN/3. Tuning the ANN.srt 37KB
  164. 23. Building a Boltzmann Machine/17. Building a Boltzmann Machine - Step 13.srt 36KB
  165. 4. Building an ANN/6. Building an ANN - Step 2.srt 36KB
  166. 3. ANN Intuition/2. The Neuron.srt 36KB
  167. 19. Building a SOM/4. Building a SOM - Step 3.srt 35KB
  168. 30. Classification Template/5. Logistic Regression Implementation - Step 5.srt 35KB
  169. 26. Building an AutoEncoder/10. Building an AutoEncoder - Step 6.srt 35KB
  170. 9. CNN Intuition/10. Softmax & Cross-Entropy.srt 35KB
  171. 23. Building a Boltzmann Machine/18. Building a Boltzmann Machine - Step 14.srt 34KB
  172. 28. Regression & Classification Intuition/5. Logistic Regression Intuition.srt 33KB
  173. 9. CNN Intuition/4. Step 1 - Convolution Operation.srt 32KB
  174. 14. RNN Intuition/3. The idea behind Recurrent Neural Networks.srt 32KB
  175. 26. Building an AutoEncoder/12. Building an AutoEncoder - Step 8.srt 31KB
  176. 9. CNN Intuition/3. What are convolutional neural networks.srt 31KB
  177. 22. Boltzmann Machine Intuition/6. Contrastive Divergence.srt 31KB
  178. 15. Building a RNN/15. Building a RNN - Step 13.srt 31KB
  179. 18. SOMs Intuition/4. K-Means Clustering (Refresher).srt 31KB
  180. 11. Homework - What's that pet/2. Homework Solution.srt 31KB
  181. 22. Boltzmann Machine Intuition/2. Boltzmann Machine.srt 30KB
  182. 14. RNN Intuition/4. The Vanishing Gradient Problem.srt 30KB
  183. 18. SOMs Intuition/5. How do Self-Organizing Maps Learn (Part 1).srt 29KB
  184. 18. SOMs Intuition/8. Reading an Advanced SOM.srt 29KB
  185. 9. CNN Intuition/6. Step 2 - Pooling.srt 29KB
  186. 14. RNN Intuition/6. Practical intuition.srt 28KB
  187. 20. Mega Case Study/3. Mega Case Study - Step 3.srt 28KB
  188. 26. Building an AutoEncoder/11. Building an AutoEncoder - Step 7.srt 28KB
  189. 3. ANN Intuition/5. How do Neural Networks learn.srt 27KB
  190. 26. Building an AutoEncoder/13. Building an AutoEncoder - Step 9.srt 27KB
  191. 10. Building a CNN/7. Building a CNN - Step 4.srt 27KB
  192. 4. Building an ANN/5. Building an ANN - Step 1.srt 27KB
  193. 3. ANN Intuition/4. How do Neural Networks work.srt 26KB
  194. 19. Building a SOM/2. Building a SOM - Step 1.srt 26KB
  195. 15. Building a RNN/6. Building a RNN - Step 4.srt 25KB
  196. 18. SOMs Intuition/10. EXTRA K-means Clustering (part 3).srt 25KB
  197. 4. Building an ANN/9. Building an ANN - Step 5.srt 25KB
  198. 23. Building a Boltzmann Machine/12. Building a Boltzmann Machine - Step 8.srt 25KB
  199. 23. Building a Boltzmann Machine/16. Building a Boltzmann Machine - Step 12.srt 25KB
  200. 29. Data Preprocessing Template/4. Data Preprocessing - Step 4.srt 24KB
  201. 26. Building an AutoEncoder/5. Building an AutoEncoder - Step 2.srt 24KB
  202. 26. Building an AutoEncoder/15. Building an AutoEncoder - Step 11.srt 24KB
  203. 1. Welcome to the course/2. What is Deep Learning.srt 24KB
  204. 26. Building an AutoEncoder/4. Building an AutoEncoder - Step 1.srt 23KB
  205. 23. Building a Boltzmann Machine/14. Building a Boltzmann Machine - Step 10.srt 23KB
  206. 22. Boltzmann Machine Intuition/3. Energy-Based Models (EBM).srt 22KB
  207. 25. AutoEncoders Intuition/2. Auto Encoders.srt 21KB
  208. 19. Building a SOM/5. Building a SOM - Step 4.srt 21KB
  209. 20. Mega Case Study/4. Mega Case Study - Step 4.srt 21KB
  210. 29. Data Preprocessing Template/6. Data Preprocessing - Step 6.srt 21KB
  211. 29. Data Preprocessing Template/5. Data Preprocessing - Step 5.srt 21KB
  212. 5. Homework Challenge - Should we say goodbye to that customer/2. Homework Solution.srt 21KB
  213. 23. Building a Boltzmann Machine/11. Building a Boltzmann Machine - Step 7.srt 21KB
  214. 23. Building a Boltzmann Machine/3. Building a Boltzmann Machine - Introduction.srt 20KB
  215. 15. Building a RNN/7. Building a RNN - Step 5.srt 20KB
  216. 29. Data Preprocessing Template/3. Data Preprocessing - Step 3.srt 19KB
  217. 19. Building a SOM/3. Building a SOM - Step 2.srt 19KB
  218. 3. ANN Intuition/6. Gradient Descent.srt 19KB
  219. 15. Building a RNN/13. Building a RNN - Step 11.srt 19KB
  220. 10. Building a CNN/4. Building a CNN - Step 1.srt 19KB
  221. 23. Building a Boltzmann Machine/5. Building a Boltzmann Machine - Step 1.srt 18KB
  222. 23. Building a Boltzmann Machine/6. Building a Boltzmann Machine - Step 2.srt 18KB
  223. 18. SOMs Intuition/6. How do Self-Organizing Maps Learn (Part 2).srt 18KB
  224. 18. SOMs Intuition/2. How do Self-Organizing Maps Work.srt 18KB
  225. 15. Building a RNN/17. Building a RNN - Step 15.srt 18KB
  226. 3. ANN Intuition/7. Stochastic Gradient Descent.srt 18KB
  227. 10. Building a CNN/13. Building a CNN - Step 10.srt 17KB
  228. 18. SOMs Intuition/9. EXTRA K-means Clustering (part 2).srt 17KB
  229. 3. ANN Intuition/3. The Activation Function.srt 17KB
  230. 23. Building a Boltzmann Machine/7. Building a Boltzmann Machine - Step 3.srt 16KB
  231. 1. Welcome to the course/4. Installing Python.srt 16KB
  232. 26. Building an AutoEncoder/6. Building an AutoEncoder - Step 3.srt 16KB
  233. 23. Building a Boltzmann Machine/10. Building a Boltzmann Machine - Step 6.srt 16KB
  234. 15. Building a RNN/9. Building a RNN - Step 7.srt 16KB
  235. 29. Data Preprocessing Template/1. Data Preprocessing - Step 1.srt 15KB
  236. 4. Building an ANN/12. Building an ANN - Step 8.srt 15KB
  237. 29. Data Preprocessing Template/2. Data Preprocessing - Step 2.srt 15KB
  238. 15. Building a RNN/16. Building a RNN - Step 14.srt 14KB
  239. 4. Building an ANN/14. Building an ANN - Step 10.srt 14KB
  240. 6. Evaluating, Improving and Tuning the ANN/2. Improving the ANN.srt 14KB
  241. 23. Building a Boltzmann Machine/13. Building a Boltzmann Machine - Step 9.srt 14KB
  242. 25. AutoEncoders Intuition/4. Training an Auto Encoder.srt 13KB
  243. 23. Building a Boltzmann Machine/15. Building a Boltzmann Machine - Step 11.srt 13KB
  244. 15. Building a RNN/4. Building a RNN - Step 2.srt 13KB
  245. 9. CNN Intuition/5. Step 1(b) - ReLU Layer.srt 12KB
  246. 10. Building a CNN/10. Building a CNN - Step 7.srt 12KB
  247. 25. AutoEncoders Intuition/6. Sparse Autoencoders.srt 12KB
  248. 15. Building a RNN/3. Building a RNN - Step 1.srt 12KB
  249. 4. Building an ANN/13. Building an ANN - Step 9.srt 12KB
  250. 15. Building a RNN/10. Building a RNN - Step 8.srt 11KB
  251. 28. Regression & Classification Intuition/2. Simple Linear Regression Intuition - Step 1.srt 11KB
  252. 22. Boltzmann Machine Intuition/7. Deep Belief Networks.srt 11KB
  253. 15. Building a RNN/5. Building a RNN - Step 3.srt 10KB
  254. 23. Building a Boltzmann Machine/9. Building a Boltzmann Machine - Step 5.srt 10KB
  255. 10. Building a CNN/9. Building a CNN - Step 6.srt 10KB
  256. 4. Building an ANN/3. Business Problem Description.srt 10KB
  257. 3. ANN Intuition/8. Backpropagation.srt 10KB
  258. 26. Building an AutoEncoder/9. Building an AutoEncoder - Step 5.srt 10KB
  259. 10. Building a CNN/8. Building a CNN - Step 5.srt 10KB
  260. 30. Classification Template/1. Logistic Regression Implementation - Step 1.srt 10KB
  261. 15. Building a RNN/14. Building a RNN - Step 12.srt 9KB
  262. 15. Building a RNN/12. Building a RNN - Step 10.srt 9KB
  263. 26. Building an AutoEncoder/14. Building an AutoEncoder - Step 10.srt 9KB
  264. 18. SOMs Intuition/7. Live SOM example.srt 9KB
  265. 20. Mega Case Study/2. Mega Case Study - Step 2.srt 9KB
  266. 10. Building a CNN/3. Introduction to CNNs.srt 9KB
  267. 9. CNN Intuition/9. Summary.srt 8KB
  268. 30. Classification Template/6. Classification Template.srt 8KB
  269. 30. Classification Template/4. Logistic Regression Implementation - Step 4.srt 8KB
  270. 25. AutoEncoders Intuition/5. Overcomplete hidden layers.srt 8KB
  271. 4. Building an ANN/11. Building an ANN - Step 7.srt 8KB
  272. 29. Data Preprocessing Template/7. Data Preprocessing Template.srt 8KB
  273. 9. CNN Intuition/2. Plan of attack.srt 7KB
  274. 14. RNN Intuition/7. EXTRA LSTM Variations.srt 7KB
  275. 20. Mega Case Study/1. Mega Case Study - Step 1.srt 7KB
  276. 22. Boltzmann Machine Intuition/4. Editing Wikipedia - Our Contribution to the World.srt 7KB
  277. 18. SOMs Intuition/1. Plan of attack.srt 7KB
  278. 15. Building a RNN/11. Building a RNN - Step 9.srt 7KB
  279. 4. Building an ANN/7. Building an ANN - Step 3.srt 7KB
  280. 22. Boltzmann Machine Intuition/8. Deep Boltzmann Machines.srt 6KB
  281. 1. Welcome to the course/1. Updates on Udemy Reviews.srt 6KB
  282. 15. Building a RNN/8. Building a RNN - Step 6.srt 6KB
  283. 30. Classification Template/2. Logistic Regression Implementation - Step 2.srt 6KB
  284. 4. Building an ANN/10. Building an ANN - Step 6.srt 6KB
  285. 28. Regression & Classification Intuition/3. Simple Linear Regression Intuition - Step 2.srt 6KB
  286. 10. Building a CNN/5. Building a CNN - Step 2.srt 6KB
  287. 10. Building a CNN/11. Building a CNN - Step 8.srt 6KB
  288. 3. ANN Intuition/1. Plan of Attack.srt 6KB
  289. 25. AutoEncoders Intuition/7. Denoising Autoencoders.srt 5KB
  290. 22. Boltzmann Machine Intuition/1. Plan of attack.srt 5KB
  291. 30. Classification Template/3. Logistic Regression Implementation - Step 3.srt 5KB
  292. 25. AutoEncoders Intuition/8. Contractive Autoencoders.srt 5KB
  293. 14. RNN Intuition/2. Plan of attack.srt 5KB
  294. 18. SOMs Intuition/3. Why revisit K-Means.srt 5KB
  295. 25. AutoEncoders Intuition/1. Plan of attack.srt 5KB
  296. 4. Building an ANN/8. Building an ANN - Step 4.srt 5KB
  297. 23. Building a Boltzmann Machine/19. Evaluating the Boltzmann Machine.html 4KB
  298. 25. AutoEncoders Intuition/10. Deep Autoencoders.srt 4KB
  299. 9. CNN Intuition/7. Step 3 - Flattening.srt 4KB
  300. 1. Welcome to the course/5. How to get the dataset.srt 3KB
  301. 10. Building a CNN/1. How to get the dataset.srt 3KB
  302. 15. Building a RNN/1. How to get the dataset.srt 3KB
  303. 19. Building a SOM/1. How to get the dataset.srt 3KB
  304. 23. Building a Boltzmann Machine/1. How to get the dataset.srt 3KB
  305. 26. Building an AutoEncoder/1. How to get the dataset.srt 3KB
  306. 4. Building an ANN/2. How to get the dataset.srt 3KB
  307. 25. AutoEncoders Intuition/9. Stacked Autoencoders.srt 3KB
  308. 31. Bonus Lectures/1. YOUR SPECIAL BONUS.html 3KB
  309. 25. AutoEncoders Intuition/3. A Note on Biases.srt 3KB
  310. 26. Building an AutoEncoder/16. THANK YOU bonus video.srt 2KB
  311. 1. Welcome to the course/3. BONUS Learning Paths.html 2KB
  312. 10. Building a CNN/6. Building a CNN - Step 3.srt 2KB
  313. 28. Regression & Classification Intuition/4. Multiple Linear Regression Intuition.srt 2KB
  314. 1. Welcome to the course/8. FAQBot!.html 2KB
  315. 16. Evaluating, Improving and Tuning the RNN/1. Evaluating the RNN.html 2KB
  316. 21. ------------------------- Part 5 - Boltzmann Machines -------------------------/1. Welcome to Part 5 - Boltzmann Machines.html 2KB
  317. 26. Building an AutoEncoder/7. Homework Challenge - Coding Exercise.html 2KB
  318. 4. Building an ANN/4. Installing Keras.html 1KB
  319. 26. Building an AutoEncoder/2. Installing PyTorch.html 1KB
  320. 23. Building a Boltzmann Machine/2. Installing PyTorch.html 1KB
  321. 4. Building an ANN/1. Prerequisites.html 1KB
  322. 16. Evaluating, Improving and Tuning the RNN/2. Improving the RNN.html 1KB
  323. 1. Welcome to the course/6. BONUS Meet Your Instructors.html 1KB
  324. 13. ---------------------- Part 3 - Recurrent Neural Networks ----------------------/1. Welcome to Part 3 - Recurrent Neural Networks.html 1KB
  325. 24. ---------------------------- Part 6 - AutoEncoders ----------------------------/1. Welcome to Part 6 - AutoEncoders.html 1KB
  326. 10. Building a CNN/2. Installing Keras.html 927B
  327. 15. Building a RNN/2. Installing Keras.html 927B
  328. 12. Evaluating, Improving and Tuning the CNN/1. Homework Challenge - Get the gold medal.html 917B
  329. 27. ------------------- Annex - Get the Machine Learning Basics -------------------/1. Annex - Get the Machine Learning Basics.html 873B
  330. 11. Homework - What's that pet/1. Homework Instruction.html 838B
  331. 16. Evaluating, Improving and Tuning the RNN/3. Tuning the RNN.html 693B
  332. 5. Homework Challenge - Should we say goodbye to that customer/1. Homework Instruction.html 682B
  333. 28. Regression & Classification Intuition/1. What You Need for Regression & Classification.html 648B
  334. 1. Welcome to the course/7. Some Additional Resources!!.html 611B
  335. 2. --------------------- Part 1 - Artificial Neural Networks ---------------------/1. Welcome to Part 1 - Artificial Neural Networks.html 516B
  336. 7. Homework Challenge - Put me one step down on the podium/1. Homework Instruction.html 426B
  337. 9. CNN Intuition/1. What You'll Need for CNN.html 386B
  338. 14. RNN Intuition/1. What You'll Need for RNN.html 366B
  339. 23. Building a Boltzmann Machine/4. Same Data Preprocessing in Parts 5 and 6.html 349B
  340. 26. Building an AutoEncoder/3. Same Data Preprocessing in Parts 5 and 6.html 348B
  341. 17. ------------------------ Part 4 - Self Organizing Maps ------------------------/1. Welcome to Part 4 - Self Organizing Maps.html 333B
  342. 8. -------------------- Part 2 - Convolutional Neural Networks --------------------/1. Welcome to Part 2 - Convolutional Neural Networks.html 323B
  343. 12. Evaluating, Improving and Tuning the CNN/2. Homework Challenge Solution - Get the gold medal.html 185B
  344. [DesireCourse.Net].url 51B
  345. [CourseClub.Me].url 48B