589689.xyz

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

  • 收录时间:2022-01-20 15:28:12
  • 文件大小:4GB
  • 下载次数:1
  • 最近下载:2022-01-20 15:28:12
  • 磁力链接:
立即下载 复制链接

文件列表

  1. 7. Building a CNN/1.1 Section 40 - Convolutional Neural Networks (CNN).zip 224MB
  2. 7. Building a CNN/8. Building a CNN - FINAL DEMO!.mp4 153MB
  3. 25. Logistic Regression Implementation/8. Logistic Regression - Step 7.mp4 119MB
  4. 7. Building a CNN/4. Building a CNN - Step 3.mp4 119MB
  5. 4. Building an ANN/5. Building an ANN - Step 2.mp4 111MB
  6. 7. Building a CNN/3. Building a CNN - Step 2.mp4 107MB
  7. 24. Data Preprocessing Template/8. Data Preprocessing - Step 7.mp4 102MB
  8. 4. Building an ANN/8. Building an ANN - Step 5.mp4 101MB
  9. 7. Building a CNN/6. Building a CNN - Step 5.mp4 98MB
  10. 24. Data Preprocessing Template/6. Data Preprocessing - Step 5.mp4 89MB
  11. 25. Logistic Regression Implementation/3. Logistic Regression - Step 2.mp4 85MB
  12. 4. Building an ANN/6. Building an ANN - Step 3.mp4 75MB
  13. 24. Data Preprocessing Template/4. Data Preprocessing - Step 3.mp4 72MB
  14. 7. Building a CNN/2. Building a CNN - Step 1.mp4 71MB
  15. 24. Data Preprocessing Template/5. Data Preprocessing - Step 4.mp4 69MB
  16. 24. Data Preprocessing Template/7. Data Preprocessing - Step 6.mp4 68MB
  17. 4. Building an ANN/3. Building an ANN - Step 1.mp4 66MB
  18. 4. Building an ANN/7. Building an ANN - Step 4.mp4 65MB
  19. 24. Data Preprocessing Template/2. Data Preprocessing - Step 1.mp4 54MB
  20. 25. Logistic Regression Implementation/7. Logistic Regression - Step 6.mp4 53MB
  21. 9. RNN Intuition/6. Practical intuition.mp4 53MB
  22. 21. Building an AutoEncoder/17. THANK YOU bonus video.mp4 52MB
  23. 21. Building an AutoEncoder/9. Building an AutoEncoder - Step 4.mp4 50MB
  24. 9. RNN Intuition/5. LSTMs.mp4 46MB
  25. 18. Building a Boltzmann Machine/8. Building a Boltzmann Machine - Step 4.mp4 46MB
  26. 25. Logistic Regression Implementation/5. Logistic Regression - Step 4.mp4 45MB
  27. 25. Logistic Regression Implementation/2. Logistic Regression - Step 1.mp4 45MB
  28. 13. SOMs Intuition/8. Reading an Advanced SOM.mp4 43MB
  29. 25. Logistic Regression Implementation/4. Logistic Regression - Step 3.mp4 43MB
  30. 18. Building a Boltzmann Machine/17. Building a Boltzmann Machine - Step 13.mp4 43MB
  31. 6. CNN Intuition/8. Step 4 - Full Connection.mp4 43MB
  32. 18. Building a Boltzmann Machine/18. Building a Boltzmann Machine - Step 14.mp4 40MB
  33. 6. CNN Intuition/6. Step 2 - Pooling.mp4 40MB
  34. 7. Building a CNN/5. Building a CNN - Step 4.mp4 40MB
  35. 10. Building a RNN/14. Building a RNN - Step 13.mp4 40MB
  36. 21. Building an AutoEncoder/11. Building an AutoEncoder - Step 6.mp4 38MB
  37. 9. RNN Intuition/3. The idea behind Recurrent Neural Networks.mp4 37MB
  38. 10. Building a RNN/5. Building a RNN - Step 4.mp4 37MB
  39. 14. Building a SOM/5. Building a SOM - Step 3.mp4 36MB
  40. 15. Mega Case Study/4. Mega Case Study - Step 3.mp4 35MB
  41. 21. Building an AutoEncoder/13. Building an AutoEncoder - Step 8.mp4 34MB
  42. 21. Building an AutoEncoder/12. Building an AutoEncoder - Step 7.mp4 34MB
  43. 6. CNN Intuition/10. Softmax & Cross-Entropy.mp4 33MB
  44. 17. Boltzmann Machine Intuition/4. Restricted Boltzmann Machine.mp4 32MB
  45. 21. Building an AutoEncoder/14. Building an AutoEncoder - Step 9.mp4 32MB
  46. 1. Welcome to the course/1. What is Deep Learning.mp4 31MB
  47. 6. CNN Intuition/4. Step 1 - Convolution Operation.mp4 31MB
  48. 18. Building a Boltzmann Machine/16. Building a Boltzmann Machine - Step 12.mp4 31MB
  49. 14. Building a SOM/3. Building a SOM - Step 1.mp4 31MB
  50. 25. Logistic Regression Implementation/6. Logistic Regression - Step 5.mp4 31MB
  51. 3. ANN Intuition/3. The Neuron.mp4 30MB
  52. 6. CNN Intuition/3. What are convolutional neural networks.mp4 30MB
  53. 10. Building a RNN/12. Building a RNN - Step 11.mp4 29MB
  54. 18. Building a Boltzmann Machine/12. Building a Boltzmann Machine - Step 8.mp4 29MB
  55. 23. Regression & Classification Intuition/5. Logistic Regression Intuition.mp4 29MB
  56. 9. RNN Intuition/4. The Vanishing Gradient Problem.mp4 29MB
  57. 14. Building a SOM/6. Building a SOM - Step 4.mp4 29MB
  58. 21. Building an AutoEncoder/16. Building an AutoEncoder - Step 11.mp4 28MB
  59. 21. Building an AutoEncoder/6. Building an AutoEncoder - Step 2.mp4 28MB
  60. 3. ANN Intuition/6. How do Neural Networks learn.mp4 27MB
  61. 10. Building a RNN/6. Building a RNN - Step 5.mp4 26MB
  62. 21. Building an AutoEncoder/5. Building an AutoEncoder - Step 1.mp4 26MB
  63. 13. SOMs Intuition/5. How do Self-Organizing Maps Learn (Part 1).mp4 25MB
  64. 17. Boltzmann Machine Intuition/1. Boltzmann Machine.mp4 25MB
  65. 17. Boltzmann Machine Intuition/5. Contrastive Divergence.mp4 25MB
  66. 18. Building a Boltzmann Machine/14. Building a Boltzmann Machine - Step 10.mp4 24MB
  67. 3. ANN Intuition/5. How do Neural Networks work.mp4 24MB
  68. 18. Building a Boltzmann Machine/11. Building a Boltzmann Machine - Step 7.mp4 23MB
  69. 15. Mega Case Study/5. Mega Case Study - Step 4.mp4 23MB
  70. 10. Building a RNN/16. Building a RNN - Step 15.mp4 22MB
  71. 20. AutoEncoders Intuition/1. Auto Encoders.mp4 22MB
  72. 10. Building a RNN/15. Building a RNN - Step 14.mp4 22MB
  73. 13. SOMs Intuition/4. K-Means Clustering (Refresher).mp4 21MB
  74. 18. Building a Boltzmann Machine/5. Building a Boltzmann Machine - Step 1.mp4 21MB
  75. 18. Building a Boltzmann Machine/3. Building a Boltzmann Machine - Introduction.mp4 21MB
  76. 10. Building a RNN/8. Building a RNN - Step 7.mp4 21MB
  77. 18. Building a Boltzmann Machine/6. Building a Boltzmann Machine - Step 2.mp4 21MB
  78. 1. Welcome to the course/2. Updates on Udemy Reviews.mp4 20MB
  79. 21. Building an AutoEncoder/7. Building an AutoEncoder - Step 3.mp4 20MB
  80. 14. Building a SOM/4. Building a SOM - Step 2.mp4 19MB
  81. 18. Building a Boltzmann Machine/10. Building a Boltzmann Machine - Step 6.mp4 19MB
  82. 3. ANN Intuition/7. Gradient Descent.mp4 19MB
  83. 13. SOMs Intuition/10. EXTRA K-means Clustering (part 3).mp4 18MB
  84. 17. Boltzmann Machine Intuition/3. Editing Wikipedia - Our Contribution to the World.mp4 18MB
  85. 18. Building a Boltzmann Machine/7. Building a Boltzmann Machine - Step 3.mp4 18MB
  86. 3. ANN Intuition/8. Stochastic Gradient Descent.mp4 17MB
  87. 18. Building a Boltzmann Machine/15. Building a Boltzmann Machine - Step 11.mp4 17MB
  88. 4. Building an ANN/1. Business Problem Description.mp4 16MB
  89. 24. Data Preprocessing Template/3. Data Preprocessing - Step 2.mp4 16MB
  90. 13. SOMs Intuition/2. How do Self-Organizing Maps Work.mp4 16MB
  91. 10. Building a RNN/4. Building a RNN - Step 3.mp4 16MB
  92. 17. Boltzmann Machine Intuition/2. Energy-Based Models (EBM).mp4 16MB
  93. 10. Building a RNN/3. Building a RNN - Step 2.mp4 16MB
  94. 13. SOMs Intuition/6. How do Self-Organizing Maps Learn (Part 2).mp4 15MB
  95. 18. Building a Boltzmann Machine/13. Building a Boltzmann Machine - Step 9.mp4 15MB
  96. 3. ANN Intuition/4. The Activation Function.mp4 15MB
  97. 6. CNN Intuition/5. Step 1(b) - ReLU Layer.mp4 14MB
  98. 10. Building a RNN/2. Building a RNN - Step 1.mp4 14MB
  99. 10. Building a RNN/13. Building a RNN - Step 12.mp4 13MB
  100. 10. Building a RNN/9. Building a RNN - Step 8.mp4 13MB
  101. 13. SOMs Intuition/7. Live SOM example.mp4 13MB
  102. 13. SOMs Intuition/9. EXTRA K-means Clustering (part 2).mp4 12MB
  103. 21. Building an AutoEncoder/10. Building an AutoEncoder - Step 5.mp4 12MB
  104. 20. AutoEncoders Intuition/5. Sparse Autoencoders.mp4 12MB
  105. 10. Building a RNN/11. Building a RNN - Step 10.mp4 11MB
  106. 21. Building an AutoEncoder/15. Building an AutoEncoder - Step 10.mp4 11MB
  107. 20. AutoEncoders Intuition/3. Training an Auto Encoder.mp4 11MB
  108. 18. Building a Boltzmann Machine/9. Building a Boltzmann Machine - Step 5.mp4 11MB
  109. 3. ANN Intuition/9. Backpropagation.mp4 11MB
  110. 17. Boltzmann Machine Intuition/6. Deep Belief Networks.mp4 10MB
  111. 15. Mega Case Study/3. Mega Case Study - Step 2.mp4 10MB
  112. 23. Regression & Classification Intuition/2. Simple Linear Regression Intuition - Step 1.mp4 9MB
  113. 10. Building a RNN/10. Building a RNN - Step 9.mp4 8MB
  114. 6. CNN Intuition/9. Summary.mp4 8MB
  115. 9. RNN Intuition/7. EXTRA LSTM Variations.mp4 7MB
  116. 10. Building a RNN/7. Building a RNN - Step 6.mp4 7MB
  117. 17. Boltzmann Machine Intuition/8. How to get the dataset.mp4 6MB
  118. 14. Building a SOM/2. How to get the dataset.mp4 6MB
  119. 21. Building an AutoEncoder/2. How to get the dataset.mp4 6MB
  120. 20. AutoEncoders Intuition/4. Overcomplete hidden layers.mp4 6MB
  121. 23. Regression & Classification Intuition/3. Simple Linear Regression Intuition - Step 2.mp4 5MB
  122. 25. Logistic Regression Implementation/1.1 Machine Learning A-Z (Codes and Datasets).zip 5MB
  123. 24. Data Preprocessing Template/1.1 Machine Learning A-Z (Codes and Datasets).zip 5MB
  124. 4. Building an ANN/2.1 Machine Learning A-Z (Codes and Datasets).zip 5MB
  125. 6. CNN Intuition/2. Plan of attack.mp4 5MB
  126. 17. Boltzmann Machine Intuition/7. Deep Boltzmann Machines.mp4 5MB
  127. 3. ANN Intuition/2. Plan of Attack.mp4 5MB
  128. 20. AutoEncoders Intuition/6. Denoising Autoencoders.mp4 5MB
  129. 13. SOMs Intuition/1. Plan of attack.mp4 4MB
  130. 20. AutoEncoders Intuition/7. Contractive Autoencoders.mp4 4MB
  131. 15. Mega Case Study/2. Mega Case Study - Step 1.mp4 4MB
  132. 9. RNN Intuition/2. Plan of attack.mp4 4MB
  133. 20. AutoEncoders Intuition/8. Stacked Autoencoders.mp4 4MB
  134. 13. SOMs Intuition/3. Why revisit K-Means.mp4 3MB
  135. 19. ---------------------------- Part 6 - AutoEncoders ----------------------------/2. Plan of attack.mp4 3MB
  136. 6. CNN Intuition/7. Step 3 - Flattening.mp4 3MB
  137. 16. ------------------------- Part 5 - Boltzmann Machines -------------------------/2. Plan of attack.mp4 3MB
  138. 20. AutoEncoders Intuition/9. Deep Autoencoders.mp4 3MB
  139. 20. AutoEncoders Intuition/2. A Note on Biases.mp4 2MB
  140. 23. Regression & Classification Intuition/4. Multiple Linear Regression Intuition.mp4 2MB
  141. 10. Building a RNN/1.1 Part 3 - Recurrent Neural Networks.zip 50KB
  142. 18. Building a Boltzmann Machine/8. Building a Boltzmann Machine - Step 4.srt 42KB
  143. 21. Building an AutoEncoder/9. Building an AutoEncoder - Step 4.srt 41KB
  144. 9. RNN Intuition/5. LSTMs.srt 39KB
  145. 7. Building a CNN/8. Building a CNN - FINAL DEMO!.srt 39KB
  146. 6. CNN Intuition/8. Step 4 - Full Connection.srt 39KB
  147. 17. Boltzmann Machine Intuition/4. Restricted Boltzmann Machine.srt 38KB
  148. 18. Building a Boltzmann Machine/17. Building a Boltzmann Machine - Step 13.srt 36KB
  149. 3. ANN Intuition/3. The Neuron.srt 36KB
  150. 14. Building a SOM/5. Building a SOM - Step 3.srt 35KB
  151. 21. Building an AutoEncoder/11. Building an AutoEncoder - Step 6.srt 35KB
  152. 6. CNN Intuition/10. Softmax & Cross-Entropy.srt 35KB
  153. 18. Building a Boltzmann Machine/18. Building a Boltzmann Machine - Step 14.srt 34KB
  154. 23. Regression & Classification Intuition/5. Logistic Regression Intuition.srt 33KB
  155. 24. Data Preprocessing Template/8. Data Preprocessing - Step 7.srt 33KB
  156. 6. CNN Intuition/4. Step 1 - Convolution Operation.srt 32KB
  157. 9. RNN Intuition/3. The idea behind Recurrent Neural Networks.srt 32KB
  158. 21. Building an AutoEncoder/13. Building an AutoEncoder - Step 8.srt 31KB
  159. 6. CNN Intuition/3. What are convolutional neural networks.srt 31KB
  160. 17. Boltzmann Machine Intuition/5. Contrastive Divergence.srt 31KB
  161. 4. Building an ANN/5. Building an ANN - Step 2.srt 31KB
  162. 10. Building a RNN/14. Building a RNN - Step 13.srt 31KB
  163. 13. SOMs Intuition/4. K-Means Clustering (Refresher).srt 31KB
  164. 17. Boltzmann Machine Intuition/1. Boltzmann Machine.srt 30KB
  165. 9. RNN Intuition/4. The Vanishing Gradient Problem.srt 30KB
  166. 13. SOMs Intuition/5. How do Self-Organizing Maps Learn (Part 1).srt 29KB
  167. 7. Building a CNN/3. Building a CNN - Step 2.srt 29KB
  168. 7. Building a CNN/4. Building a CNN - Step 3.srt 29KB
  169. 13. SOMs Intuition/8. Reading an Advanced SOM.srt 29KB
  170. 6. CNN Intuition/6. Step 2 - Pooling.srt 29KB
  171. 9. RNN Intuition/6. Practical intuition.srt 28KB
  172. 15. Mega Case Study/4. Mega Case Study - Step 3.srt 28KB
  173. 21. Building an AutoEncoder/12. Building an AutoEncoder - Step 7.srt 28KB
  174. 3. ANN Intuition/6. How do Neural Networks learn.srt 27KB
  175. 21. Building an AutoEncoder/14. Building an AutoEncoder - Step 9.srt 27KB
  176. 3. ANN Intuition/5. How do Neural Networks work.srt 26KB
  177. 14. Building a SOM/3. Building a SOM - Step 1.srt 26KB
  178. 4. Building an ANN/8. Building an ANN - Step 5.srt 26KB
  179. 24. Data Preprocessing Template/4. Data Preprocessing - Step 3.srt 26KB
  180. 10. Building a RNN/5. Building a RNN - Step 4.srt 25KB
  181. 13. SOMs Intuition/10. EXTRA K-means Clustering (part 3).srt 25KB
  182. 18. Building a Boltzmann Machine/12. Building a Boltzmann Machine - Step 8.srt 25KB
  183. 18. Building a Boltzmann Machine/16. Building a Boltzmann Machine - Step 12.srt 25KB
  184. 25. Logistic Regression Implementation/8. Logistic Regression - Step 7.srt 24KB
  185. 21. Building an AutoEncoder/6. Building an AutoEncoder - Step 2.srt 24KB
  186. 21. Building an AutoEncoder/16. Building an AutoEncoder - Step 11.srt 24KB
  187. 1. Welcome to the course/1. What is Deep Learning.srt 24KB
  188. 24. Data Preprocessing Template/6. Data Preprocessing - Step 5.srt 24KB
  189. 4. Building an ANN/6. Building an ANN - Step 3.srt 23KB
  190. 25. Logistic Regression Implementation/3. Logistic Regression - Step 2.srt 23KB
  191. 21. Building an AutoEncoder/5. Building an AutoEncoder - Step 1.srt 23KB
  192. 18. Building a Boltzmann Machine/14. Building a Boltzmann Machine - Step 10.srt 23KB
  193. 7. Building a CNN/6. Building a CNN - Step 5.srt 22KB
  194. 24. Data Preprocessing Template/7. Data Preprocessing - Step 6.srt 22KB
  195. 17. Boltzmann Machine Intuition/2. Energy-Based Models (EBM).srt 22KB
  196. 20. AutoEncoders Intuition/1. Auto Encoders.srt 21KB
  197. 14. Building a SOM/6. Building a SOM - Step 4.srt 21KB
  198. 15. Mega Case Study/5. Mega Case Study - Step 4.srt 21KB
  199. 18. Building a Boltzmann Machine/11. Building a Boltzmann Machine - Step 7.srt 21KB
  200. 18. Building a Boltzmann Machine/3. Building a Boltzmann Machine - Introduction.srt 20KB
  201. 4. Building an ANN/7. Building an ANN - Step 4.srt 20KB
  202. 10. Building a RNN/6. Building a RNN - Step 5.srt 20KB
  203. 24. Data Preprocessing Template/5. Data Preprocessing - Step 4.srt 19KB
  204. 14. Building a SOM/4. Building a SOM - Step 2.srt 19KB
  205. 3. ANN Intuition/7. Gradient Descent.srt 19KB
  206. 10. Building a RNN/12. Building a RNN - Step 11.srt 19KB
  207. 18. Building a Boltzmann Machine/5. Building a Boltzmann Machine - Step 1.srt 18KB
  208. 18. Building a Boltzmann Machine/6. Building a Boltzmann Machine - Step 2.srt 18KB
  209. 13. SOMs Intuition/6. How do Self-Organizing Maps Learn (Part 2).srt 18KB
  210. 13. SOMs Intuition/2. How do Self-Organizing Maps Work.srt 18KB
  211. 7. Building a CNN/2. Building a CNN - Step 1.srt 18KB
  212. 10. Building a RNN/16. Building a RNN - Step 15.srt 18KB
  213. 3. ANN Intuition/8. Stochastic Gradient Descent.srt 18KB
  214. 24. Data Preprocessing Template/2. Data Preprocessing - Step 1.srt 17KB
  215. 4. Building an ANN/3. Building an ANN - Step 1.srt 17KB
  216. 13. SOMs Intuition/9. EXTRA K-means Clustering (part 2).srt 17KB
  217. 3. ANN Intuition/4. The Activation Function.srt 17KB
  218. 18. Building a Boltzmann Machine/7. Building a Boltzmann Machine - Step 3.srt 16KB
  219. 21. Building an AutoEncoder/7. Building an AutoEncoder - Step 3.srt 16KB
  220. 18. Building a Boltzmann Machine/10. Building a Boltzmann Machine - Step 6.srt 16KB
  221. 10. Building a RNN/8. Building a RNN - Step 7.srt 16KB
  222. 25. Logistic Regression Implementation/2. Logistic Regression - Step 1.srt 16KB
  223. 25. Logistic Regression Implementation/7. Logistic Regression - Step 6.srt 15KB
  224. 10. Building a RNN/15. Building a RNN - Step 14.srt 14KB
  225. 18. Building a Boltzmann Machine/13. Building a Boltzmann Machine - Step 9.srt 14KB
  226. 20. AutoEncoders Intuition/3. Training an Auto Encoder.srt 13KB
  227. 18. Building a Boltzmann Machine/15. Building a Boltzmann Machine - Step 11.srt 13KB
  228. 10. Building a RNN/3. Building a RNN - Step 2.srt 13KB
  229. 6. CNN Intuition/5. Step 1(b) - ReLU Layer.srt 12KB
  230. 20. AutoEncoders Intuition/5. Sparse Autoencoders.srt 12KB
  231. 10. Building a RNN/2. Building a RNN - Step 1.srt 12KB
  232. 25. Logistic Regression Implementation/4. Logistic Regression - Step 3.srt 12KB
  233. 25. Logistic Regression Implementation/5. Logistic Regression - Step 4.srt 12KB
  234. 7. Building a CNN/5. Building a CNN - Step 4.srt 11KB
  235. 10. Building a RNN/9. Building a RNN - Step 8.srt 11KB
  236. 23. Regression & Classification Intuition/2. Simple Linear Regression Intuition - Step 1.srt 11KB
  237. 17. Boltzmann Machine Intuition/6. Deep Belief Networks.srt 11KB
  238. 10. Building a RNN/4. Building a RNN - Step 3.srt 10KB
  239. 18. Building a Boltzmann Machine/9. Building a Boltzmann Machine - Step 5.srt 10KB
  240. 4. Building an ANN/1. Business Problem Description.srt 10KB
  241. 25. Logistic Regression Implementation/6. Logistic Regression - Step 5.srt 10KB
  242. 3. ANN Intuition/9. Backpropagation.srt 10KB
  243. 21. Building an AutoEncoder/10. Building an AutoEncoder - Step 5.srt 10KB
  244. 10. Building a RNN/13. Building a RNN - Step 12.srt 9KB
  245. 10. Building a RNN/11. Building a RNN - Step 10.srt 9KB
  246. 21. Building an AutoEncoder/15. Building an AutoEncoder - Step 10.srt 9KB
  247. 13. SOMs Intuition/7. Live SOM example.srt 9KB
  248. 15. Mega Case Study/3. Mega Case Study - Step 2.srt 9KB
  249. 6. CNN Intuition/9. Summary.srt 8KB
  250. 20. AutoEncoders Intuition/4. Overcomplete hidden layers.srt 8KB
  251. 6. CNN Intuition/2. Plan of attack.srt 7KB
  252. 9. RNN Intuition/7. EXTRA LSTM Variations.srt 7KB
  253. 15. Mega Case Study/2. Mega Case Study - Step 1.srt 7KB
  254. 17. Boltzmann Machine Intuition/3. Editing Wikipedia - Our Contribution to the World.srt 7KB
  255. 13. SOMs Intuition/1. Plan of attack.srt 7KB
  256. 10. Building a RNN/10. Building a RNN - Step 9.srt 7KB
  257. 17. Boltzmann Machine Intuition/7. Deep Boltzmann Machines.srt 6KB
  258. 10. Building a RNN/7. Building a RNN - Step 6.srt 6KB
  259. 23. Regression & Classification Intuition/3. Simple Linear Regression Intuition - Step 2.srt 6KB
  260. 24. Data Preprocessing Template/3. Data Preprocessing - Step 2.srt 6KB
  261. 3. ANN Intuition/2. Plan of Attack.srt 6KB
  262. 20. AutoEncoders Intuition/6. Denoising Autoencoders.srt 5KB
  263. 16. ------------------------- Part 5 - Boltzmann Machines -------------------------/2. Plan of attack.srt 5KB
  264. 20. AutoEncoders Intuition/7. Contractive Autoencoders.srt 5KB
  265. 9. RNN Intuition/2. Plan of attack.srt 5KB
  266. 13. SOMs Intuition/3. Why revisit K-Means.srt 5KB
  267. 19. ---------------------------- Part 6 - AutoEncoders ----------------------------/2. Plan of attack.srt 5KB
  268. 18. Building a Boltzmann Machine/19. Evaluating the Boltzmann Machine.html 4KB
  269. 1. Welcome to the course/8. Your Shortcut To Becoming A Better Data Scientist!.html 4KB
  270. 20. AutoEncoders Intuition/9. Deep Autoencoders.srt 4KB
  271. 6. CNN Intuition/7. Step 3 - Flattening.srt 4KB
  272. 14. Building a SOM/2. How to get the dataset.srt 3KB
  273. 17. Boltzmann Machine Intuition/8. How to get the dataset.srt 3KB
  274. 21. Building an AutoEncoder/2. How to get the dataset.srt 3KB
  275. 20. AutoEncoders Intuition/8. Stacked Autoencoders.srt 3KB
  276. 26. Bonus Lectures/1. YOUR SPECIAL BONUS.html 3KB
  277. 1. Welcome to the course/6. FAQBot!.html 3KB
  278. 20. AutoEncoders Intuition/2. A Note on Biases.srt 3KB
  279. 21. Building an AutoEncoder/17. THANK YOU bonus video.srt 2KB
  280. 23. Regression & Classification Intuition/4. Multiple Linear Regression Intuition.srt 2KB
  281. 1. Welcome to the course/2. Updates on Udemy Reviews.srt 2KB
  282. 10. Building a RNN/1. IMPORTANT NOTE.html 2KB
  283. 11. Evaluating and Improving the RNN/1. Evaluating the RNN.html 2KB
  284. 4. Building an ANN/2. IMPORTANT NOTE.html 2KB
  285. 16. ------------------------- Part 5 - Boltzmann Machines -------------------------/1. Welcome to Part 5 - Boltzmann Machines.html 2KB
  286. 21. Building an AutoEncoder/8. Homework Challenge - Coding Exercise.html 2KB
  287. 7. Building a CNN/1. IMPORTANT NOTE.html 1KB
  288. 21. Building an AutoEncoder/3. Installing PyTorch.html 1KB
  289. 1. Welcome to the course/3. BONUS Learning Paths.html 1KB
  290. 18. Building a Boltzmann Machine/2. Installing PyTorch.html 1KB
  291. 11. Evaluating and Improving the RNN/2. Improving the RNN.html 1KB
  292. 7. Building a CNN/7. Quick Note.html 1KB
  293. 1. Welcome to the course/4. BONUS Meet Your Instructors.html 1KB
  294. 8. ---------------------- Part 3 - Recurrent Neural Networks ----------------------/1. Welcome to Part 3 - Recurrent Neural Networks.html 1KB
  295. 19. ---------------------------- Part 6 - AutoEncoders ----------------------------/1. Welcome to Part 6 - AutoEncoders.html 1KB
  296. 25. Logistic Regression Implementation/1. Important Instructions.html 970B
  297. 24. Data Preprocessing Template/1. Important Instructions.html 929B
  298. 22. ------------------- Annex - Get the Machine Learning Basics -------------------/1. Annex - Get the Machine Learning Basics.html 899B
  299. 14. Building a SOM/1. IMPORTANT NOTE.html 794B
  300. 18. Building a Boltzmann Machine/1. IMPORTANT NOTE.html 681B
  301. 15. Mega Case Study/1. IMPORTANT NOTE.html 679B
  302. 21. Building an AutoEncoder/1. IMPORTANT NOTE.html 675B
  303. 23. Regression & Classification Intuition/1. What You Need for Regression & Classification.html 648B
  304. 1. Welcome to the course/5. Some Additional Resources!!.html 611B
  305. 4. Building an ANN/4. Check out our free course on ANN for Regression.html 533B
  306. 6. CNN Intuition/1. What You'll Need for CNN.html 375B
  307. 3. ANN Intuition/1. What You'll Need for ANN.html 374B
  308. 9. RNN Intuition/1. What You'll Need for RNN.html 366B
  309. 18. Building a Boltzmann Machine/4. Same Data Preprocessing in Parts 5 and 6.html 349B
  310. 21. Building an AutoEncoder/4. Same Data Preprocessing in Parts 5 and 6.html 348B
  311. 12. ------------------------ Part 4 - Self Organizing Maps ------------------------/1. Welcome to Part 4 - Self Organizing Maps.html 333B
  312. 1. Welcome to the course/7. Get the materials.html 330B
  313. 2. --------------------- Part 1 - Artificial Neural Networks ---------------------/1. Welcome to Part 1 - Artificial Neural Networks.html 309B
  314. 5. -------------------- Part 2 - Convolutional Neural Networks --------------------/1. Welcome to Part 2 - Convolutional Neural Networks.html 280B
  315. 0. Websites you may like/[FCS Forum].url 133B
  316. 0. Websites you may like/[FreeCourseSite.com].url 127B
  317. 0. Websites you may like/[CourseClub.ME].url 122B