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[FreeCourseLab.com] Udemy - Zero to Deep Learning™ with Python and Keras

文件类型 收录时间 最后活跃 资源热度 文件大小 文件数量
视频 2019-9-17 10:31 2024-7-3 08:52 108 1.86 GB 142
磁力链接
magnet:?xt=urn:btih:5737267f67f7a4f8d1fef878d051f8fa9db957b2
迅雷链接
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOjU3MzcyNjdmNjdmN2E0ZjhkMWZlZjg3OGQwNTFmOGZhOWRiOTU3YjJaWg==
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[FreeCourseLab.com] Udemy - Zero to Deep Learning™ with Python and Keras的二维码
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FreeCourseLab com Udemy - Zero to Deep Learning™ with Python and Keras

文件列表
  1. 1. Welcome to the course!/1. Welcome to the course!.mp427.38MB
  2. 1. Welcome to the course!/2. Introduction.mp433.87MB
  3. 1. Welcome to the course!/3. Real world applications of deep learning.mp423.61MB
  4. 1. Welcome to the course!/4. Download and install Anaconda.mp425.6MB
  5. 1. Welcome to the course!/5. Installation Video Guide.mp461.14MB
  6. 1. Welcome to the course!/7. Course Folder Walkthrough.mp419.24MB
  7. 1. Welcome to the course!/8. Your first deep learning model.mp432.9MB
  8. 2. Data/1. Section 2 Intro.mp422.25MB
  9. 2. Data/10. Exercise 1 Solution.mp49.42MB
  10. 2. Data/11. Exercise 2 Presentation.mp41.92MB
  11. 2. Data/12. Exercise 2 Solution.mp413.52MB
  12. 2. Data/13. Exercise 3 Presentation.mp41.74MB
  13. 2. Data/14. Exercise 3 Solution.mp47.15MB
  14. 2. Data/15. Exercise 4 Presentation.mp41.51MB
  15. 2. Data/16. Exercise 4 Solution.mp44.2MB
  16. 2. Data/17. Exercise 5 Presentation.mp42.12MB
  17. 2. Data/18. Exercise 5 Solution.mp47.81MB
  18. 2. Data/2. Tabular data.mp411.74MB
  19. 2. Data/3. Data exploration with Pandas code along.mp430.94MB
  20. 2. Data/4. Visual data Exploration.mp49.15MB
  21. 2. Data/5. Plotting with Matplotlib.mp432.85MB
  22. 2. Data/6. Unstructured Data.mp411.33MB
  23. 2. Data/7. Images and Sound in Jupyter.mp414.02MB
  24. 2. Data/8. Feature Engineering.mp45.82MB
  25. 2. Data/9. Exercise 1 Presentation.mp43.25MB
  26. 3. Machine Learning/1. Section 3 Intro.mp438.97MB
  27. 3. Machine Learning/10. Evaluating Performance code along.mp410.35MB
  28. 3. Machine Learning/11. Classification.mp414.2MB
  29. 3. Machine Learning/12. Classification code along.mp422.87MB
  30. 3. Machine Learning/13. Overfitting.mp49.39MB
  31. 3. Machine Learning/14. Cross Validation.mp412.38MB
  32. 3. Machine Learning/15. Cross Validation code along.mp49.71MB
  33. 3. Machine Learning/16. Confusion matrix.mp411.28MB
  34. 3. Machine Learning/17. Confusion Matrix code along.mp48.65MB
  35. 3. Machine Learning/18. Feature Preprocessing code along.mp416.01MB
  36. 3. Machine Learning/19. Exercise 1 Presentation.mp46.45MB
  37. 3. Machine Learning/2. Machine Learning Problems.mp49.31MB
  38. 3. Machine Learning/20. Exercise 1 solution.mp437.31MB
  39. 3. Machine Learning/21. Exercise 2 Presentation.mp47.4MB
  40. 3. Machine Learning/22. Exercise 2 solution.mp443.21MB
  41. 3. Machine Learning/3. Supervised Learning.mp410.42MB
  42. 3. Machine Learning/4. Linear Regression.mp49.77MB
  43. 3. Machine Learning/5. Cost Function.mp46.01MB
  44. 3. Machine Learning/6. Cost Function code along.mp417.9MB
  45. 3. Machine Learning/7. Finding the best model.mp45.1MB
  46. 3. Machine Learning/8. Linear Regression code along.mp439.87MB
  47. 3. Machine Learning/9. Evaluating Performance.mp49.04MB
  48. 4. Deep Learning Intro/1. Section 4 Intro.mp430.93MB
  49. 4. Deep Learning Intro/10. Exercise 1 Presentation.mp44.75MB
  50. 4. Deep Learning Intro/11. Exercise 1 Solution.mp424.77MB
  51. 4. Deep Learning Intro/12. Exercise 2 Presentation.mp43.03MB
  52. 4. Deep Learning Intro/13. Exercise 2 Solution.mp425.2MB
  53. 4. Deep Learning Intro/14. Exercise 3 Presentation.mp42.82MB
  54. 4. Deep Learning Intro/15. Exercise 3 Solution.mp420.61MB
  55. 4. Deep Learning Intro/16. Exercise 4 Presentation.mp41.93MB
  56. 4. Deep Learning Intro/17. Exercise 4 Solution.mp413.6MB
  57. 4. Deep Learning Intro/2. Deep Learning successes.mp410.15MB
  58. 4. Deep Learning Intro/3. Neural Networks.mp49.91MB
  59. 4. Deep Learning Intro/4. Deeper Networks.mp48.47MB
  60. 4. Deep Learning Intro/5. Neural Networks code along.mp421.11MB
  61. 4. Deep Learning Intro/6. Multiple Outputs.mp410.32MB
  62. 4. Deep Learning Intro/7. Multiclass classification code along.mp433.94MB
  63. 4. Deep Learning Intro/8. Activation Functions.mp48.51MB
  64. 4. Deep Learning Intro/9. Feed forward.mp49.98MB
  65. 5. Gradient Descent/1. Section 5 Intro.mp430.76MB
  66. 5. Gradient Descent/10. Learning Rate code along.mp433.17MB
  67. 5. Gradient Descent/11. Gradient Descent.mp46.42MB
  68. 5. Gradient Descent/12. Gradient Descent code along.mp413.2MB
  69. 5. Gradient Descent/13. EWMA.mp47.37MB
  70. 5. Gradient Descent/14. Optimizers.mp49.18MB
  71. 5. Gradient Descent/15. Optimizers code along.mp410.69MB
  72. 5. Gradient Descent/16. Initialization code along.mp413.36MB
  73. 5. Gradient Descent/17. Inner Layers Visualization code along.mp432.28MB
  74. 5. Gradient Descent/18. Exercise 1 Presentation.mp43.52MB
  75. 5. Gradient Descent/19. Exercise 1 Solution.mp417.85MB
  76. 5. Gradient Descent/2. Derivatives and Gradient.mp410.47MB
  77. 5. Gradient Descent/20. Exercise 2 Presentation.mp42.44MB
  78. 5. Gradient Descent/21. Exercise 2 Solution.mp411.01MB
  79. 5. Gradient Descent/22. Exercise 3 Presentation.mp42.95MB
  80. 5. Gradient Descent/23. Exercise 3 Solution.mp412.56MB
  81. 5. Gradient Descent/24. Exercise 4 Presentation.mp43.69MB
  82. 5. Gradient Descent/25. Exercise 4 Solution.mp411.16MB
  83. 5. Gradient Descent/26. Tensorboard.mp48.29MB
  84. 5. Gradient Descent/3. Backpropagation intuition.mp47.21MB
  85. 5. Gradient Descent/4. Chain Rule.mp412.46MB
  86. 5. Gradient Descent/5. Derivative Calculation.mp47.2MB
  87. 5. Gradient Descent/6. Fully Connected Backpropagation.mp412.5MB
  88. 5. Gradient Descent/7. Matrix Notation.mp48.56MB
  89. 5. Gradient Descent/8. Numpy Arrays code along.mp419.43MB
  90. 5. Gradient Descent/9. Learning Rate.mp43.68MB
  91. 6. Convolutional Neural Networks/1. Section 6 Intro.mp435.44MB
  92. 6. Convolutional Neural Networks/10. Convolution in 2 D.mp46.67MB
  93. 6. Convolutional Neural Networks/11. Image Filters code along.mp46.41MB
  94. 6. Convolutional Neural Networks/12. Convolutional Layers.mp412.32MB
  95. 6. Convolutional Neural Networks/13. Convolutional Layers code along.mp414.41MB
  96. 6. Convolutional Neural Networks/14. Pooling Layers.mp43.06MB
  97. 6. Convolutional Neural Networks/15. Pooling Layers code along.mp45.27MB
  98. 6. Convolutional Neural Networks/16. Convolutional Neural Networks.mp44.51MB
  99. 6. Convolutional Neural Networks/17. Convolutional Neural Networks code along.mp413.97MB
  100. 6. Convolutional Neural Networks/18. Weights in CNNs.mp45.23MB
  101. 6. Convolutional Neural Networks/19. Beyond Images.mp45.27MB
  102. 6. Convolutional Neural Networks/2. Features from Pixels.mp47.96MB
  103. 6. Convolutional Neural Networks/20. Exercise 1 Presentation.mp417.26MB
  104. 6. Convolutional Neural Networks/21. Exercise 1 Solution.mp412.87MB
  105. 6. Convolutional Neural Networks/22. Exercise 2 Presentation.mp423.7MB
  106. 6. Convolutional Neural Networks/23. Exercise 2 Solution.mp410.72MB
  107. 6. Convolutional Neural Networks/3. MNIST Classification.mp43.94MB
  108. 6. Convolutional Neural Networks/4. MNIST Classification code along.mp419.63MB
  109. 6. Convolutional Neural Networks/5. Beyond Pixels.mp47.34MB
  110. 6. Convolutional Neural Networks/6. Images as Tensors.mp410.4MB
  111. 6. Convolutional Neural Networks/7. Tensor Math code along.mp417.19MB
  112. 6. Convolutional Neural Networks/8. Convolution in 1 D.mp46.63MB
  113. 6. Convolutional Neural Networks/9. Convolution in 1 D code along.mp45.14MB
  114. 8. Recurrent Neural Networks/1. Section 8 Intro.mp424.47MB
  115. 8. Recurrent Neural Networks/10. Exercise 1 Presentation.mp410.66MB
  116. 8. Recurrent Neural Networks/11. Exercise 1 Solution.mp47.95MB
  117. 8. Recurrent Neural Networks/12. Exercise 2 Presentation.mp48.22MB
  118. 8. Recurrent Neural Networks/2. Time Series.mp410.43MB
  119. 8. Recurrent Neural Networks/3. Sequence problems.mp48.76MB
  120. 8. Recurrent Neural Networks/4. Vanilla RNN.mp45.64MB
  121. 8. Recurrent Neural Networks/5. LSTM and GRU.mp411.47MB
  122. 8. Recurrent Neural Networks/6. Time Series Forecasting code along.mp416.13MB
  123. 8. Recurrent Neural Networks/7. Time Series Forecasting with LSTM code along.mp49.45MB
  124. 8. Recurrent Neural Networks/8. Rolling Windows.mp45.08MB
  125. 8. Recurrent Neural Networks/9. Rolling Windows code along.mp421.13MB
  126. 9. Improving performance/1. Section 9 Intro.mp419.19MB
  127. 9. Improving performance/10. Image Generator code along.mp415.32MB
  128. 9. Improving performance/11. Hyperparameter search.mp47.15MB
  129. 9. Improving performance/12. Embeddings.mp46.55MB
  130. 9. Improving performance/13. Embeddings code along.mp45.73MB
  131. 9. Improving performance/14. Movies Reviews Sentiment Analysis code along.mp426.73MB
  132. 9. Improving performance/15. Exercise 1 Presentation.mp47.64MB
  133. 9. Improving performance/17. Exercise 2 Presentation.mp45.5MB
  134. 9. Improving performance/19. Exercise 3 Presentation.mp423.87MB
  135. 9. Improving performance/2. Learning curves.mp45.46MB
  136. 9. Improving performance/3. Learning curves code along.mp418.94MB
  137. 9. Improving performance/4. Batch Normalization.mp43.83MB
  138. 9. Improving performance/5. Batch Normalization code along.mp415.01MB
  139. 9. Improving performance/6. Dropout.mp45.96MB
  140. 9. Improving performance/7. Dropout and Regularization code along.mp46.29MB
  141. 9. Improving performance/8. Data Augmentation.mp46.08MB
  142. 9. Improving performance/9. Continuous Learning.mp44.84MB
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