589689.xyz

[UdemyCourseDownloader] Deep Learning Advanced NLP and RNNs

  • 收录时间:2019-03-01 21:15:56
  • 文件大小:3GB
  • 下载次数:93
  • 最近下载:2021-01-19 02:26:12
  • 磁力链接:
立即下载 复制链接

文件列表

  1. 8. Appendix/2. Windows-Focused Environment Setup 2018.mp4 193MB
  2. 8. Appendix/3. How to How to install Numpy, Theano, Tensorflow, etc....mp4 166MB
  3. 2. Review/6. CNN Code (part 1).mp4 149MB
  4. 8. Appendix/10. What order should I take your courses in (part 2).mp4 123MB
  5. 8. Appendix/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 116MB
  6. 5. Attention/5. Attention Code 1.mp4 100MB
  7. 8. Appendix/9. What order should I take your courses in (part 1).mp4 88MB
  8. 4. Sequence-to-sequence models (Seq2Seq)/7. Seq2Seq in Code 1.mp4 84MB
  9. 4. Sequence-to-sequence models (Seq2Seq)/5. Poetry Revisited Code 1.mp4 83MB
  10. 8. Appendix/6. How to Code by Yourself (part 1).mp4 82MB
  11. 6. Memory Networks/3. Memory Networks Code 1.mp4 80MB
  12. 8. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 78MB
  13. 5. Attention/8. Building a Chatbot without any more Code.mp4 76MB
  14. 4. Sequence-to-sequence models (Seq2Seq)/6. Poetry Revisited Code 2.mp4 67MB
  15. 7. Basics Review/2. (Review) Keras Neural Network in Code.mp4 66MB
  16. 2. Review/4. What is a CNN.mp4 62MB
  17. 5. Attention/2. Attention Theory.mp4 62MB
  18. 2. Review/7. CNN Code (part 2).mp4 59MB
  19. 2. Review/2. What is a word embedding.mp4 58MB
  20. 2. Review/10. Different Types of RNN Tasks.mp4 57MB
  21. 2. Review/8. What is an RNN.mp4 57MB
  22. 8. Appendix/7. How to Code by Yourself (part 2).mp4 56MB
  23. 2. Review/11. A Simple RNN Experiment.mp4 56MB
  24. 6. Memory Networks/5. Memory Networks Code 3.mp4 56MB
  25. 6. Memory Networks/4. Memory Networks Code 2.mp4 54MB
  26. 4. Sequence-to-sequence models (Seq2Seq)/8. Seq2Seq in Code 2.mp4 51MB
  27. 2. Review/9. GRUs and LSTMs.mp4 50MB
  28. 3. Bidirectional RNNs/2. Bidirectional RNN Experiment.mp4 49MB
  29. 3. Bidirectional RNNs/5. Image Classification Code.mp4 49MB
  30. 5. Attention/6. Attention Code 2.mp4 42MB
  31. 5. Attention/4. Helpful Implementation Details.mp4 41MB
  32. 6. Memory Networks/1. Memory Networks Section Introduction.mp4 39MB
  33. 8. Appendix/5. How to Succeed in this Course (Long Version).mp4 39MB
  34. 7. Basics Review/3. (Review) Keras Functional API.mp4 39MB
  35. 3. Bidirectional RNNs/1. Bidirectional RNNs Motivation.mp4 33MB
  36. 3. Bidirectional RNNs/4. Image Classification with Bidirectional RNNs.mp4 33MB
  37. 4. Sequence-to-sequence models (Seq2Seq)/1. Seq2Seq Theory.mp4 33MB
  38. 4. Sequence-to-sequence models (Seq2Seq)/3. Decoding in Detail and Teacher Forcing.mp4 31MB
  39. 2. Review/12. RNN Code.mp4 31MB
  40. 6. Memory Networks/2. Memory Networks Theory.mp4 30MB
  41. 7. Basics Review/1. (Review) Keras Discussion.mp4 28MB
  42. 2. Review/5. Where to get the data.mp4 27MB
  43. 3. Bidirectional RNNs/3. Bidirectional RNN Code.mp4 23MB
  44. 2. Review/1. Review Section Introduction.mp4 21MB
  45. 2. Review/13. Review Section Summary.mp4 20MB
  46. 1. Welcome/3. Where to get the code.mp4 20MB
  47. 8. Appendix/11. Python 2 vs Python 3.mp4 19MB
  48. 2. Review/3. Using word embeddings.mp4 19MB
  49. 8. Appendix/1. What is the Appendix.mp4 18MB
  50. 1. Welcome/4. How to Succeed in this Course.mp4 17MB
  51. 1. Welcome/2. Outline.mp4 16MB
  52. 4. Sequence-to-sequence models (Seq2Seq)/2. Seq2Seq Applications.mp4 16MB
  53. 6. Memory Networks/6. Memory Networks Section Summary.mp4 16MB
  54. 1. Welcome/1. Introduction.mp4 14MB
  55. 3. Bidirectional RNNs/6. Bidirectional RNNs Section Summary.mp4 14MB
  56. 5. Attention/9. Attention Section Summary.mp4 14MB
  57. 4. Sequence-to-sequence models (Seq2Seq)/9. Seq2Seq Section Summary.mp4 14MB
  58. 8. Appendix/12. BONUS Where to get discount coupons and FREE deep learning material.mp4 13MB
  59. 4. Sequence-to-sequence models (Seq2Seq)/4. Poetry Revisited.mp4 12MB
  60. 5. Attention/7. Visualizing Attention.mp4 10MB
  61. 5. Attention/1. Attention Section Introduction.mp4 8MB
  62. 5. Attention/3. Teacher Forcing.mp4 7MB
  63. 8. Appendix/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 28KB
  64. 5. Attention/2. Attention Theory.vtt 21KB
  65. 8. Appendix/10. What order should I take your courses in (part 2).vtt 20KB
  66. 8. Appendix/6. How to Code by Yourself (part 1).vtt 20KB
  67. 2. Review/6. CNN Code (part 1).vtt 17KB
  68. 8. Appendix/2. Windows-Focused Environment Setup 2018.vtt 17KB
  69. 2. Review/2. What is a word embedding.vtt 17KB
  70. 2. Review/4. What is a CNN.vtt 16KB
  71. 2. Review/8. What is an RNN.vtt 15KB
  72. 8. Appendix/9. What order should I take your courses in (part 1).vtt 14KB
  73. 2. Review/10. Different Types of RNN Tasks.vtt 13KB
  74. 5. Attention/4. Helpful Implementation Details.vtt 13KB
  75. 8. Appendix/5. How to Succeed in this Course (Long Version).vtt 13KB
  76. 8. Appendix/3. How to How to install Numpy, Theano, Tensorflow, etc....vtt 12KB
  77. 8. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.vtt 12KB
  78. 2. Review/9. GRUs and LSTMs.vtt 12KB
  79. 8. Appendix/7. How to Code by Yourself (part 2).vtt 12KB
  80. 6. Memory Networks/1. Memory Networks Section Introduction.vtt 11KB
  81. 6. Memory Networks/2. Memory Networks Theory.vtt 11KB
  82. 5. Attention/5. Attention Code 1.vtt 10KB
  83. 5. Attention/8. Building a Chatbot without any more Code.vtt 10KB
  84. 4. Sequence-to-sequence models (Seq2Seq)/5. Poetry Revisited Code 1.vtt 10KB
  85. 3. Bidirectional RNNs/1. Bidirectional RNNs Motivation.vtt 9KB
  86. 6. Memory Networks/3. Memory Networks Code 1.vtt 8KB
  87. 4. Sequence-to-sequence models (Seq2Seq)/7. Seq2Seq in Code 1.vtt 8KB
  88. 4. Sequence-to-sequence models (Seq2Seq)/1. Seq2Seq Theory.vtt 8KB
  89. 7. Basics Review/1. (Review) Keras Discussion.vtt 8KB
  90. 4. Sequence-to-sequence models (Seq2Seq)/3. Decoding in Detail and Teacher Forcing.vtt 8KB
  91. 4. Sequence-to-sequence models (Seq2Seq)/6. Poetry Revisited Code 2.vtt 7KB
  92. 2. Review/7. CNN Code (part 2).vtt 7KB
  93. 3. Bidirectional RNNs/4. Image Classification with Bidirectional RNNs.vtt 7KB
  94. 2. Review/11. A Simple RNN Experiment.vtt 7KB
  95. 7. Basics Review/2. (Review) Keras Neural Network in Code.vtt 6KB
  96. 6. Memory Networks/5. Memory Networks Code 3.vtt 6KB
  97. 3. Bidirectional RNNs/5. Image Classification Code.vtt 6KB
  98. 1. Welcome/3. Where to get the code.vtt 6KB
  99. 2. Review/5. Where to get the data.vtt 6KB
  100. 2. Review/13. Review Section Summary.vtt 6KB
  101. 4. Sequence-to-sequence models (Seq2Seq)/8. Seq2Seq in Code 2.vtt 5KB
  102. 2. Review/3. Using word embeddings.vtt 5KB
  103. 8. Appendix/11. Python 2 vs Python 3.vtt 5KB
  104. 2. Review/1. Review Section Introduction.vtt 5KB
  105. 1. Welcome/2. Outline.vtt 5KB
  106. 6. Memory Networks/4. Memory Networks Code 2.vtt 5KB
  107. 3. Bidirectional RNNs/2. Bidirectional RNN Experiment.vtt 5KB
  108. 7. Basics Review/3. (Review) Keras Functional API.vtt 5KB
  109. 6. Memory Networks/6. Memory Networks Section Summary.vtt 4KB
  110. 5. Attention/9. Attention Section Summary.vtt 4KB
  111. 4. Sequence-to-sequence models (Seq2Seq)/2. Seq2Seq Applications.vtt 4KB
  112. 4. Sequence-to-sequence models (Seq2Seq)/4. Poetry Revisited.vtt 4KB
  113. 2. Review/12. RNN Code.vtt 4KB
  114. 5. Attention/6. Attention Code 2.vtt 4KB
  115. 1. Welcome/4. How to Succeed in this Course.vtt 3KB
  116. 1. Welcome/1. Introduction.vtt 3KB
  117. 4. Sequence-to-sequence models (Seq2Seq)/9. Seq2Seq Section Summary.vtt 3KB
  118. 8. Appendix/1. What is the Appendix.vtt 3KB
  119. 8. Appendix/12. BONUS Where to get discount coupons and FREE deep learning material.vtt 3KB
  120. 5. Attention/7. Visualizing Attention.vtt 3KB
  121. 3. Bidirectional RNNs/6. Bidirectional RNNs Section Summary.vtt 3KB
  122. 5. Attention/1. Attention Section Introduction.vtt 3KB
  123. 3. Bidirectional RNNs/3. Bidirectional RNN Code.vtt 2KB
  124. 5. Attention/3. Teacher Forcing.vtt 2KB
  125. [FTU Forum].url 1KB
  126. [FreeCoursesOnline.Me].url 133B
  127. [FreeTutorials.Eu].url 129B