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[] Udemy - Modern Deep Learning in Python

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文件列表

  1. 17. Appendix/4. Windows-Focused Environment Setup 2018.mp4 186MB
  2. 15. PyTorch/1. PyTorch Basics.mp4 117MB
  3. 17. Appendix/10. Proof that using Jupyter Notebook is the same as not using it.mp4 78MB
  4. 17. Appendix/2. What's the difference between neural networks and deep learning.mp4 45MB
  5. 11. Project Facial Expression Recognition/5. Class-Based ANN in Theano.mp4 44MB
  6. 17. Appendix/5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 44MB
  7. 17. Appendix/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39MB
  8. 14. Keras/3. Keras Functional API.mp4 39MB
  9. 17. Appendix/14. What order should I take your courses in (part 2).mp4 38MB
  10. 11. Project Facial Expression Recognition/6. Class-Based ANN in TensorFlow.mp4 37MB
  11. 15. PyTorch/3. PyTorch Batch Norm.mp4 34MB
  12. 15. PyTorch/2. PyTorch Dropout.mp4 33MB
  13. 17. Appendix/13. What order should I take your courses in (part 1).mp4 29MB
  14. 9. GPU Speedup, Homework, and Other Misc Topics/1. Setting up a GPU Instance on Amazon Web Services.mp4 26MB
  15. 17. Appendix/7. How to Code by Yourself (part 1).mp4 25MB
  16. 8. TensorFlow/2. Building a neural network in TensorFlow.mp4 24MB
  17. 8. TensorFlow/3. What is a Session (And more).mp4 24MB
  18. 2. Review/1. Review of Basic Concepts.mp4 23MB
  19. 12. Modern Regularization Techniques/2. Dropout Regularization.mp4 23MB
  20. 7. Theano/2. Building a neural network in Theano.mp4 22MB
  21. 11. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.mp4 21MB
  22. 7. Theano/1. Theano Basics Variables, Functions, Expressions, Optimization.mp4 19MB
  23. 4. Momentum and adaptive learning rates/6. Adam Optimization.mp4 19MB
  24. 4. Momentum and adaptive learning rates/4. Variable and adaptive learning rates.mp4 19MB
  25. 13. Batch Normalization/3. Batch Normalization Theory.mp4 19MB
  26. 7. Theano/3. Is Theano Dead.mp4 18MB
  27. 8. TensorFlow/1. TensorFlow Basics Variables, Functions, Expressions, Optimization.mp4 17MB
  28. 13. Batch Normalization/7. Batch Normalization Theano (part 2).mp4 17MB
  29. 13. Batch Normalization/5. Batch Normalization Tensorflow (part 2).mp4 15MB
  30. 17. Appendix/8. How to Code by Yourself (part 2).mp4 15MB
  31. 14. Keras/2. Keras in Code.mp4 15MB
  32. 4. Momentum and adaptive learning rates/3. Momentum in Code.mp4 14MB
  33. 1. Introduction and Outline/1. Outline - what did you learn previously, and what will you learn in this course.mp4 14MB
  34. 3. Gradient Descent Full vs Batch vs Stochastic/2. Full vs Batch vs Stochastic Gradient Descent in code.mp4 14MB
  35. 4. Momentum and adaptive learning rates/7. Adam in Code.mp4 14MB
  36. 5. Choosing Hyperparameters/3. Grid Search in Code.mp4 14MB
  37. 6. Weight Initialization/3. Weight Initialization.mp4 14MB
  38. 11. Project Facial Expression Recognition/4. Utilities walkthrough.mp4 13MB
  39. 17. Appendix/6. How to Succeed in this Course (Long Version).mp4 13MB
  40. 14. Keras/1. Keras Discussion.mp4 11MB
  41. 2. Review/2. Where to get the MNIST dataset and Establishing a Linear Benchmark.mp4 11MB
  42. 4. Momentum and adaptive learning rates/5. Constant learning rate vs. RMSProp in Code.mp4 11MB
  43. 4. Momentum and adaptive learning rates/1. Using Momentum to Speed Up Training.mp4 11MB
  44. 4. Momentum and adaptive learning rates/2. Nesterov Momentum.mp4 11MB
  45. 11. Project Facial Expression Recognition/3. The class imbalance problem.mp4 10MB
  46. 6. Weight Initialization/2. Vanishing and Exploding Gradients.mp4 10MB
  47. 11. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.mp4 10MB
  48. 10. Transition to the 2nd Half of the Course/1. Transition to the 2nd Half of the Course.mp4 9MB
  49. 13. Batch Normalization/4. Batch Normalization Tensorflow (part 1).mp4 9MB
  50. 9. GPU Speedup, Homework, and Other Misc Topics/5. Theano vs. TensorFlow.mp4 9MB
  51. 12. Modern Regularization Techniques/4. Noise Injection.mp4 9MB
  52. 5. Choosing Hyperparameters/5. Random Search in Code.mp4 8MB
  53. 17. Appendix/12. Python 2 vs Python 3.mp4 8MB
  54. 17. Appendix/3. Manually Choosing Learning Rate and Regularization Penalty.mp4 8MB
  55. 13. Batch Normalization/6. Batch Normalization Theano (part 1).mp4 8MB
  56. 13. Batch Normalization/2. Exponentially-Smoothed Averages.mp4 7MB
  57. 9. GPU Speedup, Homework, and Other Misc Topics/4. How to Improve your Theano and Tensorflow Skills.mp4 7MB
  58. 12. Modern Regularization Techniques/3. Dropout Intuition.mp4 6MB
  59. 1. Introduction and Outline/2. Where does this course fit into your deep learning studies.mp4 6MB
  60. 3. Gradient Descent Full vs Batch vs Stochastic/1. What are full, batch, and stochastic gradient descent.mp4 6MB
  61. 17. Appendix/1. What is the Appendix.mp4 5MB
  62. 17. Appendix/11. How to Uncompress a .tar.gz file.mp4 5MB
  63. 5. Choosing Hyperparameters/2. Sampling Logarithmically.mp4 5MB
  64. 9. GPU Speedup, Homework, and Other Misc Topics/2. Can Big Data be used to Speed Up Backpropagation.mp4 5MB
  65. 6. Weight Initialization/4. Local vs. Global Minima.mp4 5MB
  66. 5. Choosing Hyperparameters/1. Hyperparameter Optimization Cross-validation, Grid Search, and Random Search.mp4 5MB
  67. 9. GPU Speedup, Homework, and Other Misc Topics/3. Exercises and Concepts Still to be Covered.mp4 4MB
  68. 12. Modern Regularization Techniques/1. Modern Regularization Techniques Section Introduction.mp4 4MB
  69. 12. Modern Regularization Techniques/5. Modern Regularization Techniques Section Summary.mp4 4MB
  70. 13. Batch Normalization/1. Batch Normalization Introduction.mp4 4MB
  71. 13. Batch Normalization/8. Noise Perspective.mp4 3MB
  72. 11. Project Facial Expression Recognition/7. Facial Expression Recognition Project Summary.mp4 3MB
  73. 6. Weight Initialization/5. Weight Initialization Section Summary.mp4 3MB
  74. 13. Batch Normalization/9. Batch Normalization Summary.mp4 3MB
  75. 5. Choosing Hyperparameters/4. Modifying Grid Search.mp4 2MB
  76. 6. Weight Initialization/1. Weight Initialization Section Introduction.mp4 2MB
  77. 16. PyTorch, CNTK, and MXNet/1. PyTorch, CNTK, and MXNet.mp4 1MB
  78. 17. Appendix/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 28KB
  79. 17. Appendix/14. What order should I take your courses in (part 2).vtt 20KB
  80. 17. Appendix/7. How to Code by Yourself (part 1).vtt 20KB
  81. 17. Appendix/4. Windows-Focused Environment Setup 2018.vtt 17KB
  82. 2. Review/1. Review of Basic Concepts.vtt 16KB
  83. 8. TensorFlow/3. What is a Session (And more).vtt 16KB
  84. 11. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.vtt 14KB
  85. 17. Appendix/13. What order should I take your courses in (part 1).vtt 14KB
  86. 11. Project Facial Expression Recognition/5. Class-Based ANN in Theano.vtt 13KB
  87. 4. Momentum and adaptive learning rates/4. Variable and adaptive learning rates.vtt 13KB
  88. 15. PyTorch/1. PyTorch Basics.vtt 13KB
  89. 17. Appendix/6. How to Succeed in this Course (Long Version).vtt 13KB
  90. 12. Modern Regularization Techniques/2. Dropout Regularization.vtt 13KB
  91. 17. Appendix/5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 12KB
  92. 13. Batch Normalization/3. Batch Normalization Theory.vtt 12KB
  93. 17. Appendix/10. Proof that using Jupyter Notebook is the same as not using it.vtt 12KB
  94. 4. Momentum and adaptive learning rates/6. Adam Optimization.vtt 12KB
  95. 17. Appendix/8. How to Code by Yourself (part 2).vtt 12KB
  96. 11. Project Facial Expression Recognition/6. Class-Based ANN in TensorFlow.vtt 12KB
  97. 7. Theano/3. Is Theano Dead.vtt 11KB
  98. 1. Introduction and Outline/1. Outline - what did you learn previously, and what will you learn in this course.vtt 10KB
  99. 6. Weight Initialization/3. Weight Initialization.vtt 9KB
  100. 17. Appendix/2. What's the difference between neural networks and deep learning.vtt 9KB
  101. 5. Choosing Hyperparameters/3. Grid Search in Code.vtt 8KB
  102. 14. Keras/1. Keras Discussion.vtt 8KB
  103. 9. GPU Speedup, Homework, and Other Misc Topics/5. Theano vs. TensorFlow.vtt 7KB
  104. 11. Project Facial Expression Recognition/3. The class imbalance problem.vtt 7KB
  105. 7. Theano/1. Theano Basics Variables, Functions, Expressions, Optimization.vtt 7KB
  106. 13. Batch Normalization/7. Batch Normalization Theano (part 2).vtt 7KB
  107. 6. Weight Initialization/2. Vanishing and Exploding Gradients.vtt 7KB
  108. 4. Momentum and adaptive learning rates/1. Using Momentum to Speed Up Training.vtt 7KB
  109. 4. Momentum and adaptive learning rates/2. Nesterov Momentum.vtt 7KB
  110. 14. Keras/2. Keras in Code.vtt 6KB
  111. 12. Modern Regularization Techniques/4. Noise Injection.vtt 6KB
  112. 4. Momentum and adaptive learning rates/7. Adam in Code.vtt 6KB
  113. 13. Batch Normalization/5. Batch Normalization Tensorflow (part 2).vtt 6KB
  114. 13. Batch Normalization/4. Batch Normalization Tensorflow (part 1).vtt 6KB
  115. 10. Transition to the 2nd Half of the Course/1. Transition to the 2nd Half of the Course.vtt 6KB
  116. 3. Gradient Descent Full vs Batch vs Stochastic/2. Full vs Batch vs Stochastic Gradient Descent in code.vtt 6KB
  117. 11. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.vtt 6KB
  118. 8. TensorFlow/1. TensorFlow Basics Variables, Functions, Expressions, Optimization.vtt 6KB
  119. 4. Momentum and adaptive learning rates/3. Momentum in Code.vtt 5KB
  120. 9. GPU Speedup, Homework, and Other Misc Topics/4. How to Improve your Theano and Tensorflow Skills.vtt 5KB
  121. 8. TensorFlow/2. Building a neural network in TensorFlow.vtt 5KB
  122. 17. Appendix/12. Python 2 vs Python 3.vtt 5KB
  123. 11. Project Facial Expression Recognition/4. Utilities walkthrough.vtt 5KB
  124. 17. Appendix/3. Manually Choosing Learning Rate and Regularization Penalty.vtt 5KB
  125. 1. Introduction and Outline/2. Where does this course fit into your deep learning studies.vtt 5KB
  126. 13. Batch Normalization/6. Batch Normalization Theano (part 1).vtt 5KB
  127. 13. Batch Normalization/2. Exponentially-Smoothed Averages.vtt 5KB
  128. 14. Keras/3. Keras Functional API.vtt 5KB
  129. 5. Choosing Hyperparameters/5. Random Search in Code.vtt 4KB
  130. 9. GPU Speedup, Homework, and Other Misc Topics/1. Setting up a GPU Instance on Amazon Web Services.vtt 4KB
  131. 2. Review/2. Where to get the MNIST dataset and Establishing a Linear Benchmark.vtt 4KB
  132. 5. Choosing Hyperparameters/1. Hyperparameter Optimization Cross-validation, Grid Search, and Random Search.vtt 4KB
  133. 12. Modern Regularization Techniques/3. Dropout Intuition.vtt 4KB
  134. 7. Theano/2. Building a neural network in Theano.vtt 4KB
  135. 9. GPU Speedup, Homework, and Other Misc Topics/2. Can Big Data be used to Speed Up Backpropagation.vtt 4KB
  136. 4. Momentum and adaptive learning rates/5. Constant learning rate vs. RMSProp in Code.vtt 4KB
  137. 17. Appendix/11. How to Uncompress a .tar.gz file.vtt 4KB
  138. 3. Gradient Descent Full vs Batch vs Stochastic/1. What are full, batch, and stochastic gradient descent.vtt 4KB
  139. 5. Choosing Hyperparameters/2. Sampling Logarithmically.vtt 3KB
  140. 17. Appendix/1. What is the Appendix.vtt 3KB
  141. 6. Weight Initialization/4. Local vs. Global Minima.vtt 3KB
  142. 12. Modern Regularization Techniques/1. Modern Regularization Techniques Section Introduction.vtt 3KB
  143. 9. GPU Speedup, Homework, and Other Misc Topics/3. Exercises and Concepts Still to be Covered.vtt 3KB
  144. 15. PyTorch/2. PyTorch Dropout.vtt 3KB
  145. 15. PyTorch/3. PyTorch Batch Norm.vtt 3KB
  146. 12. Modern Regularization Techniques/5. Modern Regularization Techniques Section Summary.vtt 2KB
  147. 13. Batch Normalization/1. Batch Normalization Introduction.vtt 2KB
  148. 13. Batch Normalization/8. Noise Perspective.vtt 2KB
  149. 13. Batch Normalization/9. Batch Normalization Summary.vtt 2KB
  150. 6. Weight Initialization/5. Weight Initialization Section Summary.vtt 2KB
  151. 5. Choosing Hyperparameters/4. Modifying Grid Search.vtt 2KB
  152. 11. Project Facial Expression Recognition/7. Facial Expression Recognition Project Summary.vtt 1KB
  153. 6. Weight Initialization/1. Weight Initialization Section Introduction.vtt 1KB
  154. 16. PyTorch, CNTK, and MXNet/1. PyTorch, CNTK, and MXNet.vtt 947B
  155. [FreeCourseLab.com].url 126B