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[FreeCourseSite.com] Udemy - Deep Learning Recurrent Neural Networks with Python

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视频 2021-6-26 04:43 2024-11-16 08:12 278 4.41 GB 97
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FreeCourseSite com Udemy - Deep Learning Recurrent Neural Networks with Python

文件列表
  1. 01 Introduction to Course/001 Introduction to Instructor and Aisciences.mp454.73MB
  2. 01 Introduction to Course/002 Focus of the Course.mp432.86MB
  3. 01 Introduction to Course/003 Request for Your Honest Review.mp428.67MB
  4. 02 Applications of RNN (Motivation)/001 Human Activity Recognition.mp450.98MB
  5. 02 Applications of RNN (Motivation)/002 Image Captioning.mp458.71MB
  6. 02 Applications of RNN (Motivation)/003 Machine Translation.mp446.92MB
  7. 02 Applications of RNN (Motivation)/004 Speech Recognition.mp441.2MB
  8. 02 Applications of RNN (Motivation)/005 Stock Price Predictions.mp463.16MB
  9. 02 Applications of RNN (Motivation)/006 When to Model RNN.mp496.49MB
  10. 02 Applications of RNN (Motivation)/007 Activity.mp414.83MB
  11. 03 DNN Overview/001 Introduction to Deep Learning Module.mp411.1MB
  12. 03 DNN Overview/002 Neuron and Perceptron.mp470.93MB
  13. 03 DNN Overview/003 DNN Architecture.mp440.19MB
  14. 03 DNN Overview/004 FeedForward FullyConnected MLP.mp425.18MB
  15. 03 DNN Overview/005 Calculating Number of Weights of DNN.mp433.29MB
  16. 03 DNN Overview/006 Number of Nuerons vs Number of Layers.mp433.48MB
  17. 03 DNN Overview/007 Discriminative vs Generative Learning.mp435.59MB
  18. 03 DNN Overview/008 Universal Approximation Therorem.mp448.82MB
  19. 03 DNN Overview/009 Why Depth.mp418.07MB
  20. 03 DNN Overview/010 Decision Boundary in DNN.mp433.32MB
  21. 03 DNN Overview/011 Bias Term.mp443.19MB
  22. 03 DNN Overview/012 Activation Function.mp443.02MB
  23. 03 DNN Overview/013 DNN Training Parameters.mp452.16MB
  24. 03 DNN Overview/014 Gradient Descent.mp440.67MB
  25. 03 DNN Overview/015 Backpropagation.mp455.83MB
  26. 03 DNN Overview/016 Training DNN Animantion.mp448.05MB
  27. 03 DNN Overview/017 Weigth Initialization.mp463.48MB
  28. 03 DNN Overview/018 Batch miniBatch Stocastic.mp453.57MB
  29. 03 DNN Overview/019 Batch Normalization.mp433.94MB
  30. 03 DNN Overview/020 Rprop Momentum.mp485.07MB
  31. 03 DNN Overview/021 Convergence Animation.mp447.67MB
  32. 03 DNN Overview/022 DropOut EarlyStopping Hyperparameters.mp477.89MB
  33. 04 RNN Architecture/001 Introduction to Module.mp419.88MB
  34. 04 RNN Architecture/002 Fixed Length Memory Model.mp449.73MB
  35. 04 RNN Architecture/003 Infinite Memory Architecture.mp459.79MB
  36. 04 RNN Architecture/004 Weight Sharing.mp477.56MB
  37. 04 RNN Architecture/005 Notations.mp445.89MB
  38. 04 RNN Architecture/006 ManyToMany Model.mp451.78MB
  39. 04 RNN Architecture/007 OneToMany Model.mp439.99MB
  40. 04 RNN Architecture/008 ManyToOne Model.mp429.84MB
  41. 04 RNN Architecture/009 Activity Many to One.mp432.35MB
  42. 04 RNN Architecture/010 ManyToMany Different Sizes Model.mp458.87MB
  43. 04 RNN Architecture/011 Activity Many to Many Nmt.mp425.14MB
  44. 04 RNN Architecture/012 Models Summary.mp421.1MB
  45. 04 RNN Architecture/013 Deep RNNs.mp440.68MB
  46. 05 Gradient Decsent in RNN/001 Introduction to Gradient Descent Module.mp432.17MB
  47. 05 Gradient Decsent in RNN/002 Example Setup.mp426.85MB
  48. 05 Gradient Decsent in RNN/003 Equations.mp437.14MB
  49. 05 Gradient Decsent in RNN/004 Loss Function.mp442.77MB
  50. 05 Gradient Decsent in RNN/005 Why Gradients.mp432.62MB
  51. 05 Gradient Decsent in RNN/006 Chain Rule.mp442.01MB
  52. 05 Gradient Decsent in RNN/007 Chain Rule in Action.mp436.89MB
  53. 05 Gradient Decsent in RNN/008 BackPropagation Through Time.mp471.16MB
  54. 05 Gradient Decsent in RNN/009 Activity.mp48.59MB
  55. 06 RNN implementation/001 Automatic Diffrenciation.mp415.57MB
  56. 06 RNN implementation/002 Automatic Diffrenciation Pytorch.mp434.07MB
  57. 06 RNN implementation/003 Language Modeling Next Word Prediction Vocabulary Index.mp420.08MB
  58. 06 RNN implementation/004 Language Modeling Next Word Prediction Vocabulary Index Embeddings.mp419.54MB
  59. 06 RNN implementation/005 Language Modeling Next Word Prediction RNN Architecture.mp419.05MB
  60. 06 RNN implementation/006 Language Modeling Next Word Prediction Python 1.mp436.35MB
  61. 06 RNN implementation/007 Language Modeling Next Word Prediction Python 2.mp449.31MB
  62. 06 RNN implementation/008 Language Modeling Next Word Prediction Python 3.mp454.01MB
  63. 06 RNN implementation/009 Language Modeling Next Word Prediction Python 4.mp432.48MB
  64. 06 RNN implementation/010 Language Modeling Next Word Prediction Python 5.mp425.19MB
  65. 06 RNN implementation/011 Language Modeling Next Word Prediction Python 6.mp490.25MB
  66. 07 Sentiment Classification using RNN/001 Vocabulary Implementation.mp472.87MB
  67. 07 Sentiment Classification using RNN/002 Vocabulary Implementation Helpers.mp435.53MB
  68. 07 Sentiment Classification using RNN/003 Vocabulary Implementation From File.mp441.59MB
  69. 07 Sentiment Classification using RNN/004 Vectorizer.mp426.32MB
  70. 07 Sentiment Classification using RNN/005 RNN Setup 1.mp449.08MB
  71. 07 Sentiment Classification using RNN/006 RNN Setup 2.mp4169.77MB
  72. 07 Sentiment Classification using RNN/007 WhatNext.mp423.2MB
  73. 08 Vanishing Gradients in RNN/001 Introduction to Better RNNs Module.mp431.19MB
  74. 08 Vanishing Gradients in RNN/002 Introduction Vanishing Gradients in RNN.mp445.55MB
  75. 08 Vanishing Gradients in RNN/003 GRU.mp457.48MB
  76. 08 Vanishing Gradients in RNN/004 GRU Optional.mp427.75MB
  77. 08 Vanishing Gradients in RNN/005 LSTM.mp436.7MB
  78. 08 Vanishing Gradients in RNN/006 LSTM Optional.mp426.29MB
  79. 08 Vanishing Gradients in RNN/007 Bidirectional RNN.mp442.25MB
  80. 08 Vanishing Gradients in RNN/008 Attention Model.mp454.69MB
  81. 08 Vanishing Gradients in RNN/009 Attention Model Optional.mp436.94MB
  82. 09 TensorFlow/001 Introduction to TensorFlow.mp442.72MB
  83. 09 TensorFlow/002 TensorFlow Text Classification Example using RNN.mp4130.38MB
  84. 10 Project I_ Book Writer/001 Introduction.mp453.46MB
  85. 10 Project I_ Book Writer/002 Data Mapping.mp473.37MB
  86. 10 Project I_ Book Writer/003 Modling RNN Architecture.mp475.2MB
  87. 10 Project I_ Book Writer/004 Modling RNN Model in TensorFlow.mp449.08MB
  88. 10 Project I_ Book Writer/005 Modling RNN Model Training.mp438.97MB
  89. 10 Project I_ Book Writer/006 Modling RNN Model Text Generation.mp472.55MB
  90. 10 Project I_ Book Writer/007 Activity.mp437.09MB
  91. 11 Project II_ Stock Price Prediction/001 Problem Statement.mp420.87MB
  92. 11 Project II_ Stock Price Prediction/002 Data Set.mp463.8MB
  93. 11 Project II_ Stock Price Prediction/003 Data Prepration.mp477.41MB
  94. 11 Project II_ Stock Price Prediction/004 RNN Model Training and Evaluation.mp4114.05MB
  95. 11 Project II_ Stock Price Prediction/005 Activity.mp425.37MB
  96. 12 Further Readings and Resourses/001 Further Readings and Resourses 1.mp470.33MB
  97. 13 Bonus Lecture/001 THANK YOU Bonus Video.mp429.69MB
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