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[CourseClub.Me] Coursera - Deep Learning Specialization

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CourseClub Me Coursera - Deep Learning Specialization

文件列表
  1. Convolutional Neural Networks/convolutional-neural-networks - 01 - Computer Vision.mp410.83MB
  2. Convolutional Neural Networks/convolutional-neural-networks - 02 - Edge Detection Example.mp415.95MB
  3. Convolutional Neural Networks/convolutional-neural-networks - 03 - More Edge Detection.mp412.17MB
  4. Convolutional Neural Networks/convolutional-neural-networks - 04 - Padding.mp414.01MB
  5. Convolutional Neural Networks/convolutional-neural-networks - 05 - Strided Convolutions.mp412.83MB
  6. Convolutional Neural Networks/convolutional-neural-networks - 06 - Convolutions Over Volume.mp414.76MB
  7. Convolutional Neural Networks/convolutional-neural-networks - 07 - One Layer of a Convolutional Network.mp423.79MB
  8. Convolutional Neural Networks/convolutional-neural-networks - 08 - Simple Convolutional Network Example.mp412.35MB
  9. Convolutional Neural Networks/convolutional-neural-networks - 09 - Pooling Layers.mp413.71MB
  10. Convolutional Neural Networks/convolutional-neural-networks - 10 - CNN Example.mp419.79MB
  11. Convolutional Neural Networks/convolutional-neural-networks - 11 - Why Convolutions.mp415.87MB
  12. Convolutional Neural Networks/convolutional-neural-networks - 12 - Yann LeCun Interview.mp4166.89MB
  13. Convolutional Neural Networks/convolutional-neural-networks - 13 - Why look at case studies.mp47.88MB
  14. Convolutional Neural Networks/convolutional-neural-networks - 14 - Classic Networks.mp426.69MB
  15. Convolutional Neural Networks/convolutional-neural-networks - 15 - ResNets.mp411.07MB
  16. Convolutional Neural Networks/convolutional-neural-networks - 16 - Why ResNets Work.mp414.85MB
  17. Convolutional Neural Networks/convolutional-neural-networks - 17 - Networks in Networks and 1x1 Convolutions.mp49.85MB
  18. Convolutional Neural Networks/convolutional-neural-networks - 18 - Inception Network Motivation.mp415.71MB
  19. Convolutional Neural Networks/convolutional-neural-networks - 19 - Inception Network.mp414.77MB
  20. Convolutional Neural Networks/convolutional-neural-networks - 20 - MobileNet.mp425.42MB
  21. Convolutional Neural Networks/convolutional-neural-networks - 21 - MobileNet Architecture.mp414.63MB
  22. Convolutional Neural Networks/convolutional-neural-networks - 22 - EfficientNet.mp49.06MB
  23. Convolutional Neural Networks/convolutional-neural-networks - 23 - Using Open-Source Implementation.mp413.52MB
  24. Convolutional Neural Networks/convolutional-neural-networks - 24 - Transfer Learning.mp415.43MB
  25. Convolutional Neural Networks/convolutional-neural-networks - 25 - Data Augmentation.mp416.52MB
  26. Convolutional Neural Networks/convolutional-neural-networks - 26 - State of Computer Vision.mp418.52MB
  27. Convolutional Neural Networks/convolutional-neural-networks - 27 - Object Localization.mp419.38MB
  28. Convolutional Neural Networks/convolutional-neural-networks - 28 - Landmark Detection.mp411.66MB
  29. Convolutional Neural Networks/convolutional-neural-networks - 29 - Object Detection.mp49.36MB
  30. Convolutional Neural Networks/convolutional-neural-networks - 30 - Convolutional Implementation of Sliding Windows.mp417.68MB
  31. Convolutional Neural Networks/convolutional-neural-networks - 31 - Bounding Box Predictions.mp425.81MB
  32. Convolutional Neural Networks/convolutional-neural-networks - 32 - Intersection Over Union.mp47.21MB
  33. Convolutional Neural Networks/convolutional-neural-networks - 33 - Non-max Suppression.mp412.44MB
  34. Convolutional Neural Networks/convolutional-neural-networks - 34 - Anchor Boxes.mp418.61MB
  35. Convolutional Neural Networks/convolutional-neural-networks - 35 - YOLO Algorithm.mp411.52MB
  36. Convolutional Neural Networks/convolutional-neural-networks - 36 - Region Proposals (Optional).mp412.13MB
  37. Convolutional Neural Networks/convolutional-neural-networks - 37 - Semantic Segmentation with U-Net.mp415.11MB
  38. Convolutional Neural Networks/convolutional-neural-networks - 38 - Transpose Convolutions.mp412.93MB
  39. Convolutional Neural Networks/convolutional-neural-networks - 39 - U-Net Architecture Intuition.mp46.02MB
  40. Convolutional Neural Networks/convolutional-neural-networks - 40 - U-Net Architecture.mp412.7MB
  41. Convolutional Neural Networks/convolutional-neural-networks - 41 - What is Face Recognition.mp414.28MB
  42. Convolutional Neural Networks/convolutional-neural-networks - 42 - One Shot Learning.mp47.44MB
  43. Convolutional Neural Networks/convolutional-neural-networks - 43 - Siamese Network.mp47.55MB
  44. Convolutional Neural Networks/convolutional-neural-networks - 44 - Triplet Loss.mp424.97MB
  45. Convolutional Neural Networks/convolutional-neural-networks - 45 - Face Verification and Binary Classification.mp49.73MB
  46. Convolutional Neural Networks/convolutional-neural-networks - 46 - What is Neural Style Transfer.mp44.57MB
  47. Convolutional Neural Networks/convolutional-neural-networks - 47 - What are deep ConvNets learning.mp414.7MB
  48. Convolutional Neural Networks/convolutional-neural-networks - 48 - Cost Function.mp46.7MB
  49. Convolutional Neural Networks/convolutional-neural-networks - 49 - Content Cost Function.mp45.66MB
  50. Convolutional Neural Networks/convolutional-neural-networks - 50 - Style Cost Function.mp419.22MB
  51. Convolutional Neural Networks/convolutional-neural-networks - 51 - 1D and 3D Generalizations.mp414.12MB
  52. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 01 - Train Dev Test sets.mp416.77MB
  53. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 02 - Bias Variance.mp413.36MB
  54. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 03 - Basic Recipe for Machine Learning.mp410.23MB
  55. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 04 - Regularization.mp414.23MB
  56. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 05 - Why Regularization Reduces Overfitting.mp410.43MB
  57. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 06 - Dropout Regularization.mp413.03MB
  58. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 07 - Understanding Dropout.mp410.82MB
  59. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 08 - Other Regularization Methods.mp411.75MB
  60. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 09 - Normalizing Inputs.mp48.89MB
  61. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 10 - Vanishing Exploding Gradients.mp410.7MB
  62. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 11 - Weight Initialization for Deep Networks.mp410.11MB
  63. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 12 - Numerical Approximation of Gradients.mp410.58MB
  64. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 13 - Gradient Checking.mp49.64MB
  65. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 14 - Gradient Checking Implementation Notes.mp49.12MB
  66. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 15 - Yoshua Bengio Interview.mp4114.19MB
  67. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 16 - Mini-batch Gradient Descent.mp419.28MB
  68. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 17 - Understanding Mini-batch Gradient Descent.mp417.71MB
  69. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 18 - Exponentially Weighted Averages.mp49.65MB
  70. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 19 - Understanding Exponentially Weighted Averages.mp415.59MB
  71. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 20 - Bias Correction in Exponentially Weighted Averages.mp49.07MB
  72. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 21 - Gradient Descent with Momentum.mp415.03MB
  73. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 22 - RMSprop.mp414.13MB
  74. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 23 - Adam Optimization Algorithm.mp413.03MB
  75. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 24 - Learning Rate Decay.mp414.09MB
  76. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 25 - The Problem of Local Optima.mp48.97MB
  77. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 26 - Yuanqing Lin Interview.mp464.23MB
  78. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 27 - Tuning Process.mp411.8MB
  79. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 28 - Using an Appropriate Scale to pick Hyperparameters.mp415.86MB
  80. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 29 - Hyperparameters Tuning in Practice Pandas vs. Caviar.mp411.58MB
  81. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 30 - Normalizing Activations in a Network.mp415.63MB
  82. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 31 - Fitting Batch Norm into a Neural Network.mp420.72MB
  83. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 32 - Why does Batch Norm work.mp422.89MB
  84. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 33 - Batch Norm at Test Time.mp49.86MB
  85. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 34 - Softmax Regression.mp417.54MB
  86. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 35 - Training a Softmax Classifier.mp414.27MB
  87. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 36 - Deep Learning Frameworks.mp410.01MB
  88. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/deep-neural-network - 37 - TensorFlow.mp424.97MB
  89. Neural Networks and Deep Learning/neural-networks-deep-learning - 01 - Welcome.mp410.21MB
  90. Neural Networks and Deep Learning/neural-networks-deep-learning - 02 - What is a Neural Network.mp49.97MB
  91. Neural Networks and Deep Learning/neural-networks-deep-learning - 03 - Supervised Learning with Neural Networks.mp412.9MB
  92. Neural Networks and Deep Learning/neural-networks-deep-learning - 04 - Why is Deep Learning taking off.mp418.64MB
  93. Neural Networks and Deep Learning/neural-networks-deep-learning - 05 - About this Course.mp44.66MB
  94. Neural Networks and Deep Learning/neural-networks-deep-learning - 06 - Geoffrey Hinton Interview.mp4191.76MB
  95. Neural Networks and Deep Learning/neural-networks-deep-learning - 07 - Binary Classification.mp415.24MB
  96. Neural Networks and Deep Learning/neural-networks-deep-learning - 08 - Logistic Regression.mp48.48MB
  97. Neural Networks and Deep Learning/neural-networks-deep-learning - 09 - Logistic Regression Cost Function.mp413.19MB
  98. Neural Networks and Deep Learning/neural-networks-deep-learning - 10 - Gradient Descent.mp417.05MB
  99. Neural Networks and Deep Learning/neural-networks-deep-learning - 11 - Derivatives.mp413.41MB
  100. Neural Networks and Deep Learning/neural-networks-deep-learning - 12 - More Derivative Examples.mp416.76MB
  101. Neural Networks and Deep Learning/neural-networks-deep-learning - 13 - Computation Graph.mp45.66MB
  102. Neural Networks and Deep Learning/neural-networks-deep-learning - 14 - Derivatives with a Computation Graph.mp421.69MB
  103. Neural Networks and Deep Learning/neural-networks-deep-learning - 15 - Logistic Regression Gradient Descent.mp411.15MB
  104. Neural Networks and Deep Learning/neural-networks-deep-learning - 16 - Gradient Descent on m Examples.mp412.17MB
  105. Neural Networks and Deep Learning/neural-networks-deep-learning - 17 - Vectorization.mp412.6MB
  106. Neural Networks and Deep Learning/neural-networks-deep-learning - 18 - More Vectorization Examples.mp410.34MB
  107. Neural Networks and Deep Learning/neural-networks-deep-learning - 19 - Vectorizing Logistic Regression.mp411.46MB
  108. Neural Networks and Deep Learning/neural-networks-deep-learning - 20 - Vectorizing Logistic Regression's Gradient Output.mp415.55MB
  109. Neural Networks and Deep Learning/neural-networks-deep-learning - 21 - Broadcasting in Python.mp416.17MB
  110. Neural Networks and Deep Learning/neural-networks-deep-learning - 22 - A Note on Python Numpy Vectors.mp412.36MB
  111. Neural Networks and Deep Learning/neural-networks-deep-learning - 23 - Quick tour of Jupyter iPython Notebooks.mp49.23MB
  112. Neural Networks and Deep Learning/neural-networks-deep-learning - 24 - Explanation of Logistic Regression Cost Function (Optional).mp410.47MB
  113. Neural Networks and Deep Learning/neural-networks-deep-learning - 25 - Pieter Abbeel Interview.mp480.04MB
  114. Neural Networks and Deep Learning/neural-networks-deep-learning - 26 - Neural Networks Overview.mp47.23MB
  115. Neural Networks and Deep Learning/neural-networks-deep-learning - 27 - Neural Network Representation.mp48.26MB
  116. Neural Networks and Deep Learning/neural-networks-deep-learning - 28 - Computing a Neural Network's Output.mp416.32MB
  117. Neural Networks and Deep Learning/neural-networks-deep-learning - 29 - Vectorizing Across Multiple Examples.mp413.86MB
  118. Neural Networks and Deep Learning/neural-networks-deep-learning - 30 - Explanation for Vectorized Implementation.mp411.97MB
  119. Neural Networks and Deep Learning/neural-networks-deep-learning - 31 - Activation Functions.mp419.93MB
  120. Neural Networks and Deep Learning/neural-networks-deep-learning - 32 - Why do you need Non-Linear Activation Functions.mp49.29MB
  121. Neural Networks and Deep Learning/neural-networks-deep-learning - 33 - Derivatives of Activation Functions.mp411.38MB
  122. Neural Networks and Deep Learning/neural-networks-deep-learning - 34 - Gradient Descent for Neural Networks.mp416.01MB
  123. Neural Networks and Deep Learning/neural-networks-deep-learning - 35 - Backpropagation Intuition (Optional).mp426.04MB
  124. Neural Networks and Deep Learning/neural-networks-deep-learning - 36 - Random Initialization.mp411.96MB
  125. Neural Networks and Deep Learning/neural-networks-deep-learning - 37 - Ian Goodfellow Interview.mp454.53MB
  126. Neural Networks and Deep Learning/neural-networks-deep-learning - 38 - Deep L-layer Neural Network.mp410.35MB
  127. Neural Networks and Deep Learning/neural-networks-deep-learning - 39 - Forward Propagation in a Deep Network.mp413.02MB
  128. Neural Networks and Deep Learning/neural-networks-deep-learning - 40 - Getting your Matrix Dimensions Right.mp417.35MB
  129. Neural Networks and Deep Learning/neural-networks-deep-learning - 41 - Why Deep Representations.mp417.59MB
  130. Neural Networks and Deep Learning/neural-networks-deep-learning - 42 - Building Blocks of Deep Neural Networks.mp412.81MB
  131. Neural Networks and Deep Learning/neural-networks-deep-learning - 43 - Forward and Backward Propagation.mp419.8MB
  132. Neural Networks and Deep Learning/neural-networks-deep-learning - 44 - Parameters vs Hyperparameters.mp410.21MB
  133. Neural Networks and Deep Learning/neural-networks-deep-learning - 45 - What does this have to do with the brain.mp46MB
  134. Sequence Models/nlp-sequence-models - 01 - Why Sequence Models.mp45.25MB
  135. Sequence Models/nlp-sequence-models - 02 - Notation.mp413.05MB
  136. Sequence Models/nlp-sequence-models - 03 - Recurrent Neural Network Model.mp423.34MB
  137. Sequence Models/nlp-sequence-models - 04 - Backpropagation Through Time.mp410.68MB
  138. Sequence Models/nlp-sequence-models - 05 - Different Types of RNNs.mp414.87MB
  139. Sequence Models/nlp-sequence-models - 06 - Language Model and Sequence Generation.mp417.67MB
  140. Sequence Models/nlp-sequence-models - 07 - Sampling Novel Sequences.mp413.7MB
  141. Sequence Models/nlp-sequence-models - 08 - Vanishing Gradients with RNNs.mp411.96MB
  142. Sequence Models/nlp-sequence-models - 09 - Gated Recurrent Unit (GRU).mp426.99MB
  143. Sequence Models/nlp-sequence-models - 10 - Long Short Term Memory (LSTM).mp418.81MB
  144. Sequence Models/nlp-sequence-models - 11 - Bidirectional RNN.mp414.25MB
  145. Sequence Models/nlp-sequence-models - 12 - Deep RNNs.mp48.58MB
  146. Sequence Models/nlp-sequence-models - 13 - Word Representation.mp415.23MB
  147. Sequence Models/nlp-sequence-models - 14 - Using Word Embeddings.mp413.76MB
  148. Sequence Models/nlp-sequence-models - 15 - Properties of Word Embeddings.mp417.39MB
  149. Sequence Models/nlp-sequence-models - 16 - Embedding Matrix.mp48.71MB
  150. Sequence Models/nlp-sequence-models - 17 - Learning Word Embeddings.mp416.05MB
  151. Sequence Models/nlp-sequence-models - 18 - Word2Vec.mp418.42MB
  152. Sequence Models/nlp-sequence-models - 19 - Negative Sampling.mp417.91MB
  153. Sequence Models/nlp-sequence-models - 20 - GloVe Word Vectors.mp415.57MB
  154. Sequence Models/nlp-sequence-models - 21 - Sentiment Classification.mp410.9MB
  155. Sequence Models/nlp-sequence-models - 22 - Debiasing Word Embeddings.mp416.69MB
  156. Sequence Models/nlp-sequence-models - 23 - Basic Models.mp410.2MB
  157. Sequence Models/nlp-sequence-models - 24 - Picking the Most Likely Sentence.mp414.14MB
  158. Sequence Models/nlp-sequence-models - 25 - Beam Search.mp417.9MB
  159. Sequence Models/nlp-sequence-models - 26 - Refinements to Beam Search.mp415.6MB
  160. Sequence Models/nlp-sequence-models - 27 - Error Analysis in Beam Search.mp414.98MB
  161. Sequence Models/nlp-sequence-models - 28 - Bleu Score (Optional).mp428.21MB
  162. Sequence Models/nlp-sequence-models - 29 - Attention Model Intuition.mp414.76MB
  163. Sequence Models/nlp-sequence-models - 30 - Attention Model.mp418.3MB
  164. Sequence Models/nlp-sequence-models - 31 - Speech Recognition.mp413.35MB
  165. Sequence Models/nlp-sequence-models - 32 - Trigger Word Detection.mp47.06MB
  166. Sequence Models/nlp-sequence-models - 33 - Transformer Network Intuition.mp410.27MB
  167. Sequence Models/nlp-sequence-models - 34 - Self-Attention.mp423.56MB
  168. Sequence Models/nlp-sequence-models - 35 - Multi-Head Attention.mp415.19MB
  169. Sequence Models/nlp-sequence-models - 36 - Transformer Network.mp421.16MB
  170. Sequence Models/nlp-sequence-models - 37 - Conclusion and Thank You!.mp45.2MB
  171. Structuring Machine Learning Projects/machine-learning-projects - 01 - Why ML Strategy.mp48.25MB
  172. Structuring Machine Learning Projects/machine-learning-projects - 02 - Orthogonalization.mp420.22MB
  173. Structuring Machine Learning Projects/machine-learning-projects - 03 - Single Number Evaluation Metric.mp413.59MB
  174. Structuring Machine Learning Projects/machine-learning-projects - 04 - Satisficing and Optimizing Metric.mp412.45MB
  175. Structuring Machine Learning Projects/machine-learning-projects - 05 - Train Dev Test Distributions.mp410.96MB
  176. Structuring Machine Learning Projects/machine-learning-projects - 06 - Size of the Dev and Test Sets.mp411.27MB
  177. Structuring Machine Learning Projects/machine-learning-projects - 07 - When to Change Dev Test Sets and Metrics.mp419.99MB
  178. Structuring Machine Learning Projects/machine-learning-projects - 08 - Why Human-level Performance.mp410.92MB
  179. Structuring Machine Learning Projects/machine-learning-projects - 09 - Avoidable Bias.mp411.21MB
  180. Structuring Machine Learning Projects/machine-learning-projects - 10 - Understanding Human-level Performance.mp418.86MB
  181. Structuring Machine Learning Projects/machine-learning-projects - 11 - Surpassing Human-level Performance.mp410.41MB
  182. Structuring Machine Learning Projects/machine-learning-projects - 12 - Improving your Model Performance.mp49.19MB
  183. Structuring Machine Learning Projects/machine-learning-projects - 13 - Andrej Karpathy Interview.mp484.01MB
  184. Structuring Machine Learning Projects/machine-learning-projects - 14 - Carrying Out Error Analysis.mp419MB
  185. Structuring Machine Learning Projects/machine-learning-projects - 15 - Cleaning Up Incorrectly Labeled Data.mp426.64MB
  186. Structuring Machine Learning Projects/machine-learning-projects - 16 - Build your First System Quickly, then Iterate.mp412.17MB
  187. Structuring Machine Learning Projects/machine-learning-projects - 17 - Training and Testing on Different Distributions.mp418.86MB
  188. Structuring Machine Learning Projects/machine-learning-projects - 18 - Bias and Variance with Mismatched Data Distributions.mp428MB
  189. Structuring Machine Learning Projects/machine-learning-projects - 19 - Addressing Data Mismatch.mp417.95MB
  190. Structuring Machine Learning Projects/machine-learning-projects - 20 - Transfer Learning.mp422.18MB
  191. Structuring Machine Learning Projects/machine-learning-projects - 21 - Multi-task Learning.mp429MB
  192. Structuring Machine Learning Projects/machine-learning-projects - 22 - What is End-to-end Deep Learning.mp419.04MB
  193. Structuring Machine Learning Projects/machine-learning-projects - 23 - Whether to use End-to-end Deep Learning.mp417.56MB
  194. Structuring Machine Learning Projects/machine-learning-projects - 24 - Ruslan Salakhutdinov Interview.mp4103.53MB
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