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[] Coursera - Neural Networks and Deep Learning

  • 收录时间:2018-12-19 17:01:21
  • 文件大小:878MB
  • 下载次数:116
  • 最近下载:2021-01-21 19:19:29
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文件列表

  1. 003.Heroes of Deep Learning (Optional)/007. Geoffrey Hinton interview.mp4 192MB
  2. 006.Heroes of Deep Learning (Optional)/026. Pieter Abbeel interview.mp4 80MB
  3. 008.Heroes of Deep Learning (Optional)/038. Ian Goodfellow interview.mp4 55MB
  4. 007.Shallow Neural Network/036. Backpropagation intuition (optional).mp4 26MB
  5. 004.Logistic Regression as a Neural Network/015. Derivatives with a Computation Graph.mp4 22MB
  6. 007.Shallow Neural Network/032. Activation functions.mp4 20MB
  7. 009.Deep Neural Network/044. Forward and Backward Propagation.mp4 20MB
  8. 002.Introduction to Deep Learning/004. Why is Deep Learning taking off.mp4 19MB
  9. 009.Deep Neural Network/042. Why deep representations.mp4 18MB
  10. 009.Deep Neural Network/041. Getting your matrix dimensions right.mp4 17MB
  11. 004.Logistic Regression as a Neural Network/011. Gradient Descent.mp4 17MB
  12. 004.Logistic Regression as a Neural Network/013. More Derivative Examples.mp4 17MB
  13. 007.Shallow Neural Network/029. Computing a Neural Network's Output.mp4 16MB
  14. 005.Python and Vectorization/022. Broadcasting in Python.mp4 16MB
  15. 007.Shallow Neural Network/035. Gradient descent for Neural Networks.mp4 16MB
  16. 005.Python and Vectorization/021. Vectorizing Logistic Regression's Gradient Output.mp4 16MB
  17. 004.Logistic Regression as a Neural Network/008. Binary Classification.mp4 15MB
  18. 007.Shallow Neural Network/030. Vectorizing across multiple examples.mp4 14MB
  19. 004.Logistic Regression as a Neural Network/012. Derivatives.mp4 13MB
  20. 004.Logistic Regression as a Neural Network/010. Logistic Regression Cost Function.mp4 13MB
  21. 009.Deep Neural Network/040. Forward Propagation in a Deep Network.mp4 13MB
  22. 002.Introduction to Deep Learning/003. Supervised Learning with Neural Networks.mp4 13MB
  23. 009.Deep Neural Network/043. Building blocks of deep neural networks.mp4 13MB
  24. 005.Python and Vectorization/018. Vectorization.mp4 13MB
  25. 005.Python and Vectorization/023. A note on python numpy vectors.mp4 12MB
  26. 004.Logistic Regression as a Neural Network/017. Gradient Descent on m Examples.mp4 12MB
  27. 007.Shallow Neural Network/031. Explanation for Vectorized Implementation.mp4 12MB
  28. 007.Shallow Neural Network/037. Random Initialization.mp4 12MB
  29. 005.Python and Vectorization/020. Vectorizing Logistic Regression.mp4 11MB
  30. 007.Shallow Neural Network/034. Derivatives of activation functions.mp4 11MB
  31. 004.Logistic Regression as a Neural Network/016. Logistic Regression Gradient Descent.mp4 11MB
  32. 005.Python and Vectorization/025. Explanation of logistic regression cost function (optional).mp4 10MB
  33. 009.Deep Neural Network/039. Deep L-layer neural network.mp4 10MB
  34. 005.Python and Vectorization/019. More Vectorization Examples.mp4 10MB
  35. 009.Deep Neural Network/045. Parameters vs Hyperparameters.mp4 10MB
  36. 001.Welcome to the Deep Learning Specialization/001. Welcome.mp4 10MB
  37. 002.Introduction to Deep Learning/002. What is a neural network.mp4 10MB
  38. 007.Shallow Neural Network/033. Why do you need non-linear activation functions.mp4 9MB
  39. 005.Python and Vectorization/024. Quick tour of Jupyter iPython Notebooks.mp4 9MB
  40. 004.Logistic Regression as a Neural Network/009. Logistic Regression.mp4 8MB
  41. 007.Shallow Neural Network/028. Neural Network Representation.mp4 8MB
  42. 007.Shallow Neural Network/027. Neural Networks Overview.mp4 7MB
  43. 009.Deep Neural Network/046. What does this have to do with the brain.mp4 6MB
  44. 004.Logistic Regression as a Neural Network/014. Computation graph.mp4 6MB
  45. 002.Introduction to Deep Learning/005. About this Course.mp4 5MB
  46. 002.Introduction to Deep Learning/006. Course Resources.mp4 2MB
  47. 003.Heroes of Deep Learning (Optional)/007. Geoffrey Hinton interview.srt 57KB
  48. 006.Heroes of Deep Learning (Optional)/026. Pieter Abbeel interview.srt 27KB
  49. 008.Heroes of Deep Learning (Optional)/038. Ian Goodfellow interview.srt 23KB
  50. 002.Introduction to Deep Learning/004. Why is Deep Learning taking off.srt 18KB
  51. 007.Shallow Neural Network/036. Backpropagation intuition (optional).srt 18KB
  52. 007.Shallow Neural Network/032. Activation functions.srt 17KB
  53. 007.Shallow Neural Network/029. Computing a Neural Network's Output.srt 17KB
  54. 004.Logistic Regression as a Neural Network/015. Derivatives with a Computation Graph.srt 16KB
  55. 004.Logistic Regression as a Neural Network/011. Gradient Descent.srt 15KB
  56. 009.Deep Neural Network/042. Why deep representations.srt 15KB
  57. 005.Python and Vectorization/022. Broadcasting in Python.srt 14KB
  58. 007.Shallow Neural Network/035. Gradient descent for Neural Networks.srt 13KB
  59. 009.Deep Neural Network/044. Forward and Backward Propagation.srt 13KB
  60. 009.Deep Neural Network/045. Parameters vs Hyperparameters.srt 13KB
  61. 004.Logistic Regression as a Neural Network/013. More Derivative Examples.srt 13KB
  62. 004.Logistic Regression as a Neural Network/017. Gradient Descent on m Examples.srt 12KB
  63. 004.Logistic Regression as a Neural Network/012. Derivatives.srt 12KB
  64. 002.Introduction to Deep Learning/003. Supervised Learning with Neural Networks.srt 12KB
  65. 009.Deep Neural Network/041. Getting your matrix dimensions right.srt 11KB
  66. 007.Shallow Neural Network/034. Derivatives of activation functions.srt 11KB
  67. 004.Logistic Regression as a Neural Network/010. Logistic Regression Cost Function.srt 11KB
  68. 009.Deep Neural Network/043. Building blocks of deep neural networks.srt 11KB
  69. 005.Python and Vectorization/021. Vectorizing Logistic Regression's Gradient Output.srt 11KB
  70. 004.Logistic Regression as a Neural Network/008. Binary Classification.srt 11KB
  71. 007.Shallow Neural Network/037. Random Initialization.srt 10KB
  72. 007.Shallow Neural Network/030. Vectorizing across multiple examples.srt 10KB
  73. 009.Deep Neural Network/040. Forward Propagation in a Deep Network.srt 10KB
  74. 002.Introduction to Deep Learning/002. What is a neural network.srt 10KB
  75. 005.Python and Vectorization/018. Vectorization.srt 10KB
  76. 005.Python and Vectorization/020. Vectorizing Logistic Regression.srt 10KB
  77. 005.Python and Vectorization/023. A note on python numpy vectors.srt 9KB
  78. 004.Logistic Regression as a Neural Network/016. Logistic Regression Gradient Descent.srt 9KB
  79. 001.Welcome to the Deep Learning Specialization/001. Welcome.srt 9KB
  80. 007.Shallow Neural Network/031. Explanation for Vectorized Implementation.srt 9KB
  81. 005.Python and Vectorization/025. Explanation of logistic regression cost function (optional).srt 8KB
  82. 007.Shallow Neural Network/028. Neural Network Representation.srt 8KB
  83. 007.Shallow Neural Network/033. Why do you need non-linear activation functions.srt 8KB
  84. 004.Logistic Regression as a Neural Network/009. Logistic Regression.srt 8KB
  85. 009.Deep Neural Network/039. Deep L-layer neural network.srt 7KB
  86. 005.Python and Vectorization/019. More Vectorization Examples.srt 7KB
  87. 007.Shallow Neural Network/027. Neural Networks Overview.srt 7KB
  88. 005.Python and Vectorization/024. Quick tour of Jupyter iPython Notebooks.srt 6KB
  89. 009.Deep Neural Network/046. What does this have to do with the brain.srt 6KB
  90. 002.Introduction to Deep Learning/005. About this Course.srt 4KB
  91. 004.Logistic Regression as a Neural Network/014. Computation graph.srt 4KB
  92. 002.Introduction to Deep Learning/006. Course Resources.srt 4KB
  93. [FCS Forum].url 133B
  94. [FreeCourseSite.com].url 127B
  95. [CourseClub.NET].url 123B
  96. [DesireCourse.Com].url 51B