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[] Udemy - Complete Guide to TensorFlow for Deep Learning with Python

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文件列表

  1. 1. Introduction/2.1 FULL_TENSORFLOW_NOTES__AND_DATA.zip.zip 300MB
  2. 1. Introduction/3.1 FULL_TENSORFLOW_NOTES__AND_DATA.zip.zip 300MB
  3. 6. TensorFlow Basics/8. TensorFlow Regression Example _ Part Two.mp4 58MB
  4. 7. Convolutional Neural Networks/13. CNN Project Exercise Solution - Part One.mp4 50MB
  5. 10. AutoEncoders/5. Stacked Autoencoder.mp4 44MB
  6. 5. Introduction to Neural Networks/11. Manual Neural Network Classification Task.mp4 41MB
  7. 9. Miscellaneous Topics/6. Tensorboard.mp4 40MB
  8. 10. AutoEncoders/2. Dimensionality Reduction with Linear Autoencoder.mp4 38MB
  9. 11. Reinforcement Learning with OpenAI Gym/8. Simple Neural Network Game.mp4 36MB
  10. 8. Recurrent Neural Networks/15. Word2Vec Code Along - Part One.mp4 36MB
  11. 8. Recurrent Neural Networks/12. Time Series Exercise Solution.mp4 35MB
  12. 7. Convolutional Neural Networks/7. MNIST Basic Approach Part Two.mp4 35MB
  13. 8. Recurrent Neural Networks/7. RNN with TensorFlow - Part One.mp4 34MB
  14. 8. Recurrent Neural Networks/16. Word2Vec Part Two.mp4 33MB
  15. 9. Miscellaneous Topics/4. Deep Nets with Tensorflow Abstractions API - Keras.mp4 33MB
  16. 11. Reinforcement Learning with OpenAI Gym/11. Policy Gradient Code Along Part Two.mp4 33MB
  17. 4. Crash Course Overview/2. NumPy Crash Course.mp4 33MB
  18. 6. TensorFlow Basics/6. TensorFlow - A Neural Network - Part Two.mp4 33MB
  19. 6. TensorFlow Basics/10. TensorFlow Classification Example - Part Two.mp4 32MB
  20. 3. What is Machine Learning/1. Machine Learning Overview.mp4 30MB
  21. 8. Recurrent Neural Networks/8. RNN with TensorFlow - Part Two.mp4 30MB
  22. 6. TensorFlow Basics/7. TensorFlow Regression Example - Part One.mp4 30MB
  23. 12. GAN - Generative Adversarial Networks/3. GAN Code Along - Part Two.mp4 29MB
  24. 9. Miscellaneous Topics/5. Deep Nets with Tensorflow Abstractions API - Layers.mp4 29MB
  25. 2. Installation and Setup/2. Installing TensorFlow Environment.mp4 28MB
  26. 6. TensorFlow Basics/12. TF Regression Exercise Solution Walkthrough.mp4 28MB
  27. 12. GAN - Generative Adversarial Networks/4. GAN Code Along - Part Three.mp4 28MB
  28. 5. Introduction to Neural Networks/6. TensorFlow Playground.mp4 27MB
  29. 7. Convolutional Neural Networks/14. CNN Project Exercise Solution - Part Two.mp4 27MB
  30. 7. Convolutional Neural Networks/8. CNN Theory Part One.mp4 27MB
  31. 7. Convolutional Neural Networks/10. CNN MNIST Code Along - Part One.mp4 26MB
  32. 11. Reinforcement Learning with OpenAI Gym/10. Policy Gradient Code Along Part One.mp4 26MB
  33. 5. Introduction to Neural Networks/10. Manual Creation of Neural Network - Part Four - Session.mp4 25MB
  34. 6. TensorFlow Basics/9. TensorFlow Classification Example - Part One.mp4 24MB
  35. 10. AutoEncoders/4. Linear Autoencoder PCA Exercise Solutions.mp4 23MB
  36. 6. TensorFlow Basics/14. TF Classification Exercise Solution Walkthrough.mp4 22MB
  37. 4. Crash Course Overview/5. SciKit Learn Preprocessing Overview.mp4 20MB
  38. 7. Convolutional Neural Networks/3. New Theory Topics.mp4 20MB
  39. 4. Crash Course Overview/4. Data Visualization Crash Course.mp4 20MB
  40. 12. GAN - Generative Adversarial Networks/2. GAN Code Along - Part One.mp4 20MB
  41. 6. TensorFlow Basics/2. TensorFlow Basic Syntax.mp4 19MB
  42. 9. Miscellaneous Topics/3. Deep Nets with Tensorflow Abstractions API - Estimator API.mp4 19MB
  43. 4. Crash Course Overview/7. Crash Course Review Exercise - Solutions.mp4 17MB
  44. 8. Recurrent Neural Networks/3. Manual Creation of RNN.mp4 17MB
  45. 8. Recurrent Neural Networks/14. Word2Vec Theory.mp4 17MB
  46. 1. Introduction/2. Course Overview -- PLEASE DON'T SKIP THIS LECTURE! Thanks ).mp4 16MB
  47. 9. Miscellaneous Topics/2. Deep Nets with Tensorflow Abstractions API - Part One.mp4 16MB
  48. 7. Convolutional Neural Networks/12. Introduction to CNN Project.mp4 16MB
  49. 6. TensorFlow Basics/15. Saving and Restoring Models.mp4 15MB
  50. 11. Reinforcement Learning with OpenAI Gym/6. Open AI Gym Observations.mp4 15MB
  51. 11. Reinforcement Learning with OpenAI Gym/7. OpenAI Gym Actions.mp4 15MB
  52. 11. Reinforcement Learning with OpenAI Gym/4. OpenAI Gym Steup.mp4 15MB
  53. 11. Reinforcement Learning with OpenAI Gym/3. Introduction to OpenAI Gym.mp4 14MB
  54. 10. AutoEncoders/1. Autoencoder Basics.mp4 14MB
  55. 11. Reinforcement Learning with OpenAI Gym/9. Policy Gradient Theory.mp4 14MB
  56. 8. Recurrent Neural Networks/11. Time Series Exercise Overview.mp4 14MB
  57. 12. GAN - Generative Adversarial Networks/1. Introduction to GANs.mp4 13MB
  58. 5. Introduction to Neural Networks/9. Manual Creation of Neural Network - Part Three - Placeholders and Variables.mp4 13MB
  59. 8. Recurrent Neural Networks/5. LSTM and GRU Theory.mp4 13MB
  60. 6. TensorFlow Basics/4. Variables and Placeholders.vtt 13MB
  61. 6. TensorFlow Basics/4. Variables and Placeholders.mp4 13MB
  62. 8. Recurrent Neural Networks/10. RNN with TensorFlow - Part Three.mp4 13MB
  63. 5. Introduction to Neural Networks/7. Manual Creation of Neural Network - Part One.mp4 13MB
  64. 7. Convolutional Neural Networks/6. MNIST Basic Approach Part One.mp4 12MB
  65. 1. Introduction/1. Introduction.mp4 12MB
  66. 6. TensorFlow Basics/5. TensorFlow - A Neural Network - Part One.mp4 12MB
  67. 5. Introduction to Neural Networks/8. Manual Creation of Neural Network - Part Two - Operations.mp4 11MB
  68. 8. Recurrent Neural Networks/2. RNN Theory.mp4 10MB
  69. 11. Reinforcement Learning with OpenAI Gym/5. Open AI Gym Env Basics.mp4 10MB
  70. 7. Convolutional Neural Networks/11. CNN MNIST Code Along - Part Two.mp4 10MB
  71. 4. Crash Course Overview/3. Pandas Crash Course.mp4 9MB
  72. 6. TensorFlow Basics/13. TF Classification Exercise.mp4 9MB
  73. 5. Introduction to Neural Networks/3. Neural Network Activation Functions.mp4 9MB
  74. 6. TensorFlow Basics/3. TensorFlow Graphs.mp4 9MB
  75. 11. Reinforcement Learning with OpenAI Gym/1. Introduction to Reinforcement Learning with OpenAI Gym.mp4 8MB
  76. 6. TensorFlow Basics/11. TF Regression Exercise.mp4 8MB
  77. 10. AutoEncoders/1.2 05-Autoencoders.zip.zip 8MB
  78. 4. Crash Course Overview/6. Crash Course Review Exercise.mp4 8MB
  79. 5. Introduction to Neural Networks/2. Introduction to Perceptron.mp4 7MB
  80. 7. Convolutional Neural Networks/5. MNIST Data Overview.mp4 7MB
  81. 7. Convolutional Neural Networks/9. CNN Theory Part Two.mp4 7MB
  82. 8. Recurrent Neural Networks/6. Introduction to RNN with TensorFlow API.mp4 6MB
  83. 10. AutoEncoders/3. Linear Autoencoder PCA Exercise Overview.mp4 6MB
  84. 8. Recurrent Neural Networks/13. Quick Note on Word2Vec.mp4 6MB
  85. 8. Recurrent Neural Networks/4. Vanishing Gradients.mp4 6MB
  86. 5. Introduction to Neural Networks/4. Cost Functions.mp4 5MB
  87. 5. Introduction to Neural Networks/5. Gradient Descent Backpropagation.mp4 5MB
  88. 7. Convolutional Neural Networks/2. Review of Neural Networks.mp4 3MB
  89. 4. Crash Course Overview/1. Crash Course Section Introduction.mp4 2MB
  90. 6. TensorFlow Basics/1. Introduction to TensorFlow.mp4 2MB
  91. 5. Introduction to Neural Networks/1. Introduction to Neural Networks.mp4 2MB
  92. 8. Recurrent Neural Networks/1. Introduction to RNN Section.mp4 2MB
  93. 7. Convolutional Neural Networks/1. Introduction to Convolutional Neural Network Section.mp4 1MB
  94. 9. Miscellaneous Topics/1.1 Miscellaneous-Topics.zip.zip 74KB
  95. 6. TensorFlow Basics/8. TensorFlow Regression Example _ Part Two.vtt 29KB
  96. 6. TensorFlow Basics/7. TensorFlow Regression Example - Part One.vtt 25KB
  97. 6. TensorFlow Basics/6. TensorFlow - A Neural Network - Part Two.vtt 25KB
  98. 10. AutoEncoders/5. Stacked Autoencoder.vtt 25KB
  99. 7. Convolutional Neural Networks/8. CNN Theory Part One.vtt 24KB
  100. 8. Recurrent Neural Networks/7. RNN with TensorFlow - Part One.vtt 24KB
  101. 3. What is Machine Learning/1. Machine Learning Overview.vtt 23KB
  102. 8. Recurrent Neural Networks/8. RNN with TensorFlow - Part Two.vtt 23KB
  103. 9. Miscellaneous Topics/6. Tensorboard.vtt 22KB
  104. 10. AutoEncoders/2. Dimensionality Reduction with Linear Autoencoder.vtt 22KB
  105. 8. Recurrent Neural Networks/15. Word2Vec Code Along - Part One.vtt 22KB
  106. 8. Recurrent Neural Networks/12. Time Series Exercise Solution.vtt 21KB
  107. 5. Introduction to Neural Networks/11. Manual Neural Network Classification Task.vtt 21KB
  108. 7. Convolutional Neural Networks/7. MNIST Basic Approach Part Two.vtt 21KB
  109. 11. Reinforcement Learning with OpenAI Gym/8. Simple Neural Network Game.vtt 21KB
  110. 7. Convolutional Neural Networks/10. CNN MNIST Code Along - Part One.vtt 20KB
  111. 4. Crash Course Overview/2. NumPy Crash Course.vtt 20KB
  112. 7. Convolutional Neural Networks/3. New Theory Topics.vtt 20KB
  113. 7. Convolutional Neural Networks/13. CNN Project Exercise Solution - Part One.vtt 19KB
  114. 6. TensorFlow Basics/9. TensorFlow Classification Example - Part One.vtt 17KB
  115. 6. TensorFlow Basics/2. TensorFlow Basic Syntax.vtt 17KB
  116. 2. Installation and Setup/2. Installing TensorFlow Environment.vtt 17KB
  117. 8. Recurrent Neural Networks/14. Word2Vec Theory.vtt 16KB
  118. 9. Miscellaneous Topics/4. Deep Nets with Tensorflow Abstractions API - Keras.vtt 16KB
  119. 6. TensorFlow Basics/12. TF Regression Exercise Solution Walkthrough.vtt 15KB
  120. 6. TensorFlow Basics/10. TensorFlow Classification Example - Part Two.vtt 15KB
  121. 8. Recurrent Neural Networks/16. Word2Vec Part Two.vtt 15KB
  122. 11. Reinforcement Learning with OpenAI Gym/11. Policy Gradient Code Along Part Two.vtt 15KB
  123. 6. TensorFlow Basics/14. TF Classification Exercise Solution Walkthrough.vtt 15KB
  124. 11. Reinforcement Learning with OpenAI Gym/10. Policy Gradient Code Along Part One.vtt 15KB
  125. 1. Introduction/2. Course Overview -- PLEASE DON'T SKIP THIS LECTURE! Thanks ).vtt 14KB
  126. 7. Convolutional Neural Networks/14. CNN Project Exercise Solution - Part Two.vtt 14KB
  127. 12. GAN - Generative Adversarial Networks/3. GAN Code Along - Part Two.vtt 14KB
  128. 12. GAN - Generative Adversarial Networks/4. GAN Code Along - Part Three.vtt 14KB
  129. 8. Recurrent Neural Networks/3. Manual Creation of RNN.vtt 14KB
  130. 5. Introduction to Neural Networks/6. TensorFlow Playground.vtt 13KB
  131. 9. Miscellaneous Topics/5. Deep Nets with Tensorflow Abstractions API - Layers.vtt 13KB
  132. 8. Recurrent Neural Networks/5. LSTM and GRU Theory.vtt 13KB
  133. 4. Crash Course Overview/5. SciKit Learn Preprocessing Overview.vtt 12KB
  134. 5. Introduction to Neural Networks/10. Manual Creation of Neural Network - Part Four - Session.vtt 12KB
  135. 11. Reinforcement Learning with OpenAI Gym/6. Open AI Gym Observations.vtt 12KB
  136. 12. GAN - Generative Adversarial Networks/2. GAN Code Along - Part One.vtt 12KB
  137. 10. AutoEncoders/1. Autoencoder Basics.vtt 11KB
  138. 7. Convolutional Neural Networks/6. MNIST Basic Approach Part One.vtt 11KB
  139. 11. Reinforcement Learning with OpenAI Gym/7. OpenAI Gym Actions.vtt 11KB
  140. 5. Introduction to Neural Networks/9. Manual Creation of Neural Network - Part Three - Placeholders and Variables.vtt 11KB
  141. 8. Recurrent Neural Networks/2. RNN Theory.vtt 11KB
  142. 11. Reinforcement Learning with OpenAI Gym/1.2 06-Reinforcement-Learning-OpenAI.zip.zip 11KB
  143. 11. Reinforcement Learning with OpenAI Gym/9. Policy Gradient Theory.vtt 11KB
  144. 11. Reinforcement Learning with OpenAI Gym/4. OpenAI Gym Steup.vtt 10KB
  145. 8. Recurrent Neural Networks/11. Time Series Exercise Overview.vtt 10KB
  146. 5. Introduction to Neural Networks/8. Manual Creation of Neural Network - Part Two - Operations.vtt 10KB
  147. 4. Crash Course Overview/4. Data Visualization Crash Course.vtt 10KB
  148. 10. AutoEncoders/4. Linear Autoencoder PCA Exercise Solutions.vtt 10KB
  149. 12. GAN - Generative Adversarial Networks/1. Introduction to GANs.vtt 10KB
  150. 6. TensorFlow Basics/5. TensorFlow - A Neural Network - Part One.vtt 10KB
  151. 9. Miscellaneous Topics/2. Deep Nets with Tensorflow Abstractions API - Part One.vtt 10KB
  152. 9. Miscellaneous Topics/3. Deep Nets with Tensorflow Abstractions API - Estimator API.vtt 10KB
  153. 8. Recurrent Neural Networks/10. RNN with TensorFlow - Part Three.vtt 9KB
  154. 6. TensorFlow Basics/15. Saving and Restoring Models.vtt 9KB
  155. 7. Convolutional Neural Networks/12. Introduction to CNN Project.vtt 9KB
  156. 5. Introduction to Neural Networks/3. Neural Network Activation Functions.vtt 8KB
  157. 11. Reinforcement Learning with OpenAI Gym/5. Open AI Gym Env Basics.vtt 8KB
  158. 4. Crash Course Overview/7. Crash Course Review Exercise - Solutions.vtt 8KB
  159. 11. Reinforcement Learning with OpenAI Gym/3. Introduction to OpenAI Gym.vtt 8KB
  160. 5. Introduction to Neural Networks/7. Manual Creation of Neural Network - Part One.vtt 8KB
  161. 6. TensorFlow Basics/3. TensorFlow Graphs.vtt 8KB
  162. 5. Introduction to Neural Networks/2. Introduction to Perceptron.vtt 7KB
  163. 6. TensorFlow Basics/13. TF Classification Exercise.vtt 7KB
  164. 7. Convolutional Neural Networks/11. CNN MNIST Code Along - Part Two.vtt 7KB
  165. 8. Recurrent Neural Networks/6. Introduction to RNN with TensorFlow API.vtt 6KB
  166. 8. Recurrent Neural Networks/4. Vanishing Gradients.vtt 6KB
  167. 4. Crash Course Overview/3. Pandas Crash Course.vtt 6KB
  168. 7. Convolutional Neural Networks/9. CNN Theory Part Two.vtt 6KB
  169. 11. Reinforcement Learning with OpenAI Gym/1. Introduction to Reinforcement Learning with OpenAI Gym.vtt 6KB
  170. 13. BONUS/1. Bonus Lecture Discounts for for My Other Courses.html 6KB
  171. 7. Convolutional Neural Networks/5. MNIST Data Overview.vtt 6KB
  172. 6. TensorFlow Basics/11. TF Regression Exercise.vtt 5KB
  173. 5. Introduction to Neural Networks/5. Gradient Descent Backpropagation.vtt 5KB
  174. 5. Introduction to Neural Networks/4. Cost Functions.vtt 5KB
  175. 8. Recurrent Neural Networks/13. Quick Note on Word2Vec.vtt 4KB
  176. 1. Introduction/1. Introduction.vtt 4KB
  177. 7. Convolutional Neural Networks/2. Review of Neural Networks.vtt 3KB
  178. 4. Crash Course Overview/6. Crash Course Review Exercise.vtt 3KB
  179. 10. AutoEncoders/3. Linear Autoencoder PCA Exercise Overview.vtt 3KB
  180. 2. Installation and Setup/1. Quick Note for MacOS and Linux Users.html 2KB
  181. 6. TensorFlow Basics/1. Introduction to TensorFlow.vtt 2KB
  182. 4. Crash Course Overview/1. Crash Course Section Introduction.vtt 2KB
  183. 8. Recurrent Neural Networks/1. Introduction to RNN Section.vtt 2KB
  184. 5. Introduction to Neural Networks/1. Introduction to Neural Networks.vtt 1KB
  185. 11. Reinforcement Learning with OpenAI Gym/2. Extra Resources for Reinforcement Learning.html 1KB
  186. 7. Convolutional Neural Networks/1. Introduction to Convolutional Neural Network Section.vtt 1KB
  187. 8. Recurrent Neural Networks/9. Quick Note on RNN Plotting Part 3.html 1020B
  188. 1. Introduction/3. FAQ - Frequently Asked Questions.html 413B
  189. 9. Miscellaneous Topics/1. Intro to Miscellaneous Topics.html 344B
  190. 10. AutoEncoders/1.1 Autoencoder Slides.html 161B
  191. 11. Reinforcement Learning with OpenAI Gym/1.1 Reinforcement Learning Slides.html 161B
  192. 3. What is Machine Learning/1.1 ML Overview Slides.html 161B
  193. 5. Introduction to Neural Networks/1.1 Introduction to NN Slides.html 161B
  194. 6. TensorFlow Basics/1.1 TF Basics Slides.html 161B
  195. 7. Convolutional Neural Networks/1.1 CNN Slides.html 161B
  196. 8. Recurrent Neural Networks/1.1 RNN Slides.html 161B
  197. 6. TensorFlow Basics/15.1 Link to notebook.html 145B
  198. [FCS Forum].url 133B
  199. [FreeCourseSite.com].url 127B
  200. [CourseClub.NET].url 123B
  201. 7. Convolutional Neural Networks/4. Quick note on MNIST lecture.html 121B