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Deep Learning Specialization

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视频 2019-2-4 16:12 2024-12-26 11:36 80 1.81 GB 150
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Deep Learning Specialization

文件列表
  1. 1. neural-networks-deep-learning/01_introduction-to-deep-learning/02_introduction-to-deep-learning/06_course-resources.mp42.23MB
  2. 4. convolutional-neural-networks/04_special-applications-face-recognition-neural-style-transfer/02_neural-style-transfer/01_what-is-neural-style-transfer.mp42.99MB
  3. 1. neural-networks-deep-learning/01_introduction-to-deep-learning/02_introduction-to-deep-learning/04_about-this-course.mp43.15MB
  4. 1. neural-networks-deep-learning/02_neural-networks-basics/01_logistic-regression-as-a-neural-network/07_computation-graph.mp44.38MB
  5. 1. neural-networks-deep-learning/04_deep-neural-networks/01_deep-neural-network/08_what-does-this-have-to-do-with-the-brain.mp44.4MB
  6. 3. machine-learning-projects/01_ml-strategy-1/01_introduction-to-ml-strategy/01_why-ml-strategy.mp44.51MB
  7. 4. convolutional-neural-networks/04_special-applications-face-recognition-neural-style-transfer/02_neural-style-transfer/04_content-cost-function.mp44.66MB
  8. 4. convolutional-neural-networks/02_deep-convolutional-models-case-studies/01_case-studies/01_why-look-at-case-studies.mp44.67MB
  9. 4. convolutional-neural-networks/04_special-applications-face-recognition-neural-style-transfer/02_neural-style-transfer/03_cost-function.mp45.2MB
  10. 4. convolutional-neural-networks/03_object-detection/01_detection-algorithms/06_intersection-over-union.mp45.47MB
  11. 1. neural-networks-deep-learning/03_shallow-neural-networks/01_shallow-neural-network/01_neural-networks-overview.mp45.59MB
  12. 1. neural-networks-deep-learning/02_neural-networks-basics/02_python-and-vectorization/07_quick-tour-of-jupyter-ipython-notebooks.mp45.87MB
  13. 4. convolutional-neural-networks/04_special-applications-face-recognition-neural-style-transfer/01_face-recognition/02_one-shot-learning.mp45.88MB
  14. 2. deep-neural-network/02_optimization-algorithms/01_optimization-algorithms/05_bias-correction-in-exponentially-weighted-averages.mp46.01MB
  15. 4. convolutional-neural-networks/04_special-applications-face-recognition-neural-style-transfer/01_face-recognition/03_siamese-network.mp46.09MB
  16. 2. deep-neural-network/03_hyperparameter-tuning-batch-normalization-and-programming-frameworks/04_introduction-to-programming-frameworks/01_deep-learning-frameworks.mp46.37MB
  17. 1. neural-networks-deep-learning/03_shallow-neural-networks/01_shallow-neural-network/02_neural-network-representation.mp46.6MB
  18. 2. deep-neural-network/02_optimization-algorithms/01_optimization-algorithms/10_the-problem-of-local-optima.mp46.88MB
  19. 2. deep-neural-network/01_practical-aspects-of-deep-learning/03_setting-up-your-optimization-problem/06_gradient-checking-implementation-notes.mp46.89MB
  20. 2. deep-neural-network/01_practical-aspects-of-deep-learning/03_setting-up-your-optimization-problem/01_normalizing-inputs.mp46.95MB
  21. 1. neural-networks-deep-learning/02_neural-networks-basics/01_logistic-regression-as-a-neural-network/02_logistic-regression.mp47.2MB
  22. 4. convolutional-neural-networks/03_object-detection/01_detection-algorithms/03_object-detection.mp47.29MB
  23. 1. neural-networks-deep-learning/01_introduction-to-deep-learning/01_welcome-to-the-deep-learning-specialization/01_welcome.mp47.36MB
  24. 1. neural-networks-deep-learning/03_shallow-neural-networks/01_shallow-neural-network/07_why-do-you-need-non-linear-activation-functions.mp47.39MB
  25. 2. deep-neural-network/03_hyperparameter-tuning-batch-normalization-and-programming-frameworks/02_batch-normalization/04_batch-norm-at-test-time.mp47.62MB
  26. 4. convolutional-neural-networks/01_foundations-of-convolutional-neural-networks/01_convolutional-neural-networks/01_computer-vision.mp47.63MB
  27. 3. machine-learning-projects/01_ml-strategy-1/02_setting-up-your-goal/04_size-of-the-dev-and-test-sets.mp47.64MB
  28. 2. deep-neural-network/02_optimization-algorithms/01_optimization-algorithms/03_exponentially-weighted-averages.mp47.65MB
  29. 3. machine-learning-projects/01_ml-strategy-1/03_comparing-to-human-level-performance/01_why-human-level-performance.mp47.75MB
  30. 1. neural-networks-deep-learning/04_deep-neural-networks/01_deep-neural-network/01_deep-l-layer-neural-network.mp47.78MB
  31. 4. convolutional-neural-networks/04_special-applications-face-recognition-neural-style-transfer/01_face-recognition/05_face-verification-and-binary-classification.mp47.87MB
  32. 2. deep-neural-network/01_practical-aspects-of-deep-learning/03_setting-up-your-optimization-problem/03_weight-initialization-for-deep-networks.mp47.88MB
  33. 2. deep-neural-network/01_practical-aspects-of-deep-learning/01_setting-up-your-machine-learning-application/03_basic-recipe-for-machine-learning.mp47.97MB
  34. 3. machine-learning-projects/01_ml-strategy-1/03_comparing-to-human-level-performance/04_surpassing-human-level-performance.mp48.05MB
  35. 1. neural-networks-deep-learning/02_neural-networks-basics/02_python-and-vectorization/02_more-vectorization-examples.mp48.08MB
  36. 2. deep-neural-network/01_practical-aspects-of-deep-learning/03_setting-up-your-optimization-problem/05_gradient-checking.mp48.08MB
  37. 4. convolutional-neural-networks/02_deep-convolutional-models-case-studies/02_practical-advices-for-using-convnets/01_using-open-source-implementation.mp48.14MB
  38. 3. machine-learning-projects/01_ml-strategy-1/03_comparing-to-human-level-performance/05_improving-your-model-performance.mp48.16MB
  39. 4. convolutional-neural-networks/03_object-detection/01_detection-algorithms/02_landmark-detection.mp48.17MB
  40. 4. convolutional-neural-networks/02_deep-convolutional-models-case-studies/01_case-studies/05_networks-in-networks-and-1x1-convolutions.mp48.19MB
  41. 2. deep-neural-network/01_practical-aspects-of-deep-learning/03_setting-up-your-optimization-problem/02_vanishing-exploding-gradients.mp48.22MB
  42. 3. machine-learning-projects/02_ml-strategy-2/01_error-analysis/03_build-your-first-system-quickly-then-iterate.mp48.28MB
  43. 2. deep-neural-network/01_practical-aspects-of-deep-learning/03_setting-up-your-optimization-problem/04_numerical-approximation-of-gradients.mp48.32MB
  44. 3. machine-learning-projects/01_ml-strategy-1/02_setting-up-your-goal/03_train-dev-test-distributions.mp48.35MB
  45. 4. convolutional-neural-networks/04_special-applications-face-recognition-neural-style-transfer/01_face-recognition/01_what-is-face-recognition.mp48.41MB
  46. 3. machine-learning-projects/01_ml-strategy-1/02_setting-up-your-goal/02_satisficing-and-optimizing-metric.mp48.47MB
  47. 1. neural-networks-deep-learning/01_introduction-to-deep-learning/02_introduction-to-deep-learning/01_what-is-a-neural-network.mp48.52MB
  48. 1. neural-networks-deep-learning/02_neural-networks-basics/01_logistic-regression-as-a-neural-network/09_logistic-regression-gradient-descent.mp48.52MB
  49. 3. machine-learning-projects/01_ml-strategy-1/03_comparing-to-human-level-performance/02_avoidable-bias.mp48.69MB
  50. 1. neural-networks-deep-learning/04_deep-neural-networks/01_deep-neural-network/07_parameters-vs-hyperparameters.mp48.7MB
  51. 1. neural-networks-deep-learning/02_neural-networks-basics/02_python-and-vectorization/08_explanation-of-logistic-regression-cost-function-optional.mp48.76MB
  52. 4. convolutional-neural-networks/03_object-detection/01_detection-algorithms/10_optional-region-proposals.mp48.8MB
  53. 2. deep-neural-network/03_hyperparameter-tuning-batch-normalization-and-programming-frameworks/01_hyperparameter-tuning/03_hyperparameters-tuning-in-practice-pandas-vs-caviar.mp48.81MB
  54. 2. deep-neural-network/01_practical-aspects-of-deep-learning/02_regularizing-your-neural-network/02_why-regularization-reduces-overfitting.mp48.87MB
  55. 2. deep-neural-network/01_practical-aspects-of-deep-learning/02_regularizing-your-neural-network/04_understanding-dropout.mp49MB
  56. 4. convolutional-neural-networks/02_deep-convolutional-models-case-studies/01_case-studies/03_resnets.mp49MB
  57. 1. neural-networks-deep-learning/02_neural-networks-basics/02_python-and-vectorization/06_a-note-on-python-numpy-vectors.mp49.04MB
  58. 2. deep-neural-network/03_hyperparameter-tuning-batch-normalization-and-programming-frameworks/01_hyperparameter-tuning/01_tuning-process.mp49.04MB
  59. 4. convolutional-neural-networks/03_object-detection/01_detection-algorithms/09_yolo-algorithm.mp49.07MB
  60. 2. deep-neural-network/02_optimization-algorithms/01_optimization-algorithms/09_learning-rate-decay.mp49.33MB
  61. 2. deep-neural-network/02_optimization-algorithms/01_optimization-algorithms/08_adam-optimization-algorithm.mp49.41MB
  62. 1. neural-networks-deep-learning/02_neural-networks-basics/02_python-and-vectorization/03_vectorizing-logistic-regression.mp49.41MB
  63. 1. neural-networks-deep-learning/02_neural-networks-basics/01_logistic-regression-as-a-neural-network/05_derivatives.mp49.53MB
  64. 1. neural-networks-deep-learning/03_shallow-neural-networks/01_shallow-neural-network/08_derivatives-of-activation-functions.mp49.6MB
  65. 1. neural-networks-deep-learning/03_shallow-neural-networks/01_shallow-neural-network/05_explanation-for-vectorized-implementation.mp49.7MB
  66. 3. machine-learning-projects/01_ml-strategy-1/02_setting-up-your-goal/01_single-number-evaluation-metric.mp49.77MB
  67. 1. neural-networks-deep-learning/03_shallow-neural-networks/01_shallow-neural-network/11_random-initialization.mp49.85MB
  68. 4. convolutional-neural-networks/01_foundations-of-convolutional-neural-networks/01_convolutional-neural-networks/03_more-edge-detection.mp49.85MB
  69. 1. neural-networks-deep-learning/04_deep-neural-networks/01_deep-neural-network/02_forward-propagation-in-a-deep-network.mp49.89MB
  70. 2. deep-neural-network/01_practical-aspects-of-deep-learning/02_regularizing-your-neural-network/05_other-regularization-methods.mp49.94MB
  71. 1. neural-networks-deep-learning/02_neural-networks-basics/01_logistic-regression-as-a-neural-network/10_gradient-descent-on-m-examples.mp410.02MB
  72. 1. neural-networks-deep-learning/02_neural-networks-basics/02_python-and-vectorization/01_vectorization.mp410.05MB
  73. 4. convolutional-neural-networks/03_object-detection/01_detection-algorithms/07_non-max-suppression.mp410.09MB
  74. 2. deep-neural-network/02_optimization-algorithms/01_optimization-algorithms/07_rmsprop.mp410.32MB
  75. 4. convolutional-neural-networks/01_foundations-of-convolutional-neural-networks/01_convolutional-neural-networks/08_simple-convolutional-network-example.mp410.39MB
  76. 1. neural-networks-deep-learning/02_neural-networks-basics/01_logistic-regression-as-a-neural-network/03_logistic-regression-cost-function.mp410.63MB
  77. 1. neural-networks-deep-learning/01_introduction-to-deep-learning/02_introduction-to-deep-learning/02_supervised-learning-with-neural-networks.mp410.64MB
  78. 1. neural-networks-deep-learning/04_deep-neural-networks/01_deep-neural-network/05_building-blocks-of-deep-neural-networks.mp410.75MB
  79. 2. deep-neural-network/01_practical-aspects-of-deep-learning/01_setting-up-your-machine-learning-application/02_bias-variance.mp410.77MB
  80. 4. convolutional-neural-networks/01_foundations-of-convolutional-neural-networks/01_convolutional-neural-networks/05_strided-convolutions.mp410.98MB
  81. 1. neural-networks-deep-learning/02_neural-networks-basics/01_logistic-regression-as-a-neural-network/01_binary-classification.mp411MB
  82. 4. convolutional-neural-networks/04_special-applications-face-recognition-neural-style-transfer/02_neural-style-transfer/02_what-are-deep-convnets-learning.mp411.26MB
  83. 2. deep-neural-network/01_practical-aspects-of-deep-learning/02_regularizing-your-neural-network/03_dropout-regularization.mp411.3MB
  84. 4. convolutional-neural-networks/04_special-applications-face-recognition-neural-style-transfer/02_neural-style-transfer/06_1d-and-3d-generalizations.mp411.32MB
  85. 4. convolutional-neural-networks/02_deep-convolutional-models-case-studies/01_case-studies/07_inception-network.mp411.37MB
  86. 4. convolutional-neural-networks/02_deep-convolutional-models-case-studies/02_practical-advices-for-using-convnets/02_transfer-learning.mp411.57MB
  87. 1. neural-networks-deep-learning/03_shallow-neural-networks/01_shallow-neural-network/04_vectorizing-across-multiple-examples.mp411.58MB
  88. 2. deep-neural-network/03_hyperparameter-tuning-batch-normalization-and-programming-frameworks/01_hyperparameter-tuning/02_using-an-appropriate-scale-to-pick-hyperparameters.mp411.64MB
  89. 2. deep-neural-network/03_hyperparameter-tuning-batch-normalization-and-programming-frameworks/02_batch-normalization/01_normalizing-activations-in-a-network.mp411.81MB
  90. 2. deep-neural-network/01_practical-aspects-of-deep-learning/02_regularizing-your-neural-network/01_regularization.mp411.9MB
  91. 4. convolutional-neural-networks/02_deep-convolutional-models-case-studies/01_case-studies/04_why-resnets-work.mp411.92MB
  92. 4. convolutional-neural-networks/01_foundations-of-convolutional-neural-networks/01_convolutional-neural-networks/04_padding.mp411.94MB
  93. 2. deep-neural-network/02_optimization-algorithms/01_optimization-algorithms/06_gradient-descent-with-momentum.mp411.95MB
  94. 4. convolutional-neural-networks/01_foundations-of-convolutional-neural-networks/01_convolutional-neural-networks/09_pooling-layers.mp412.11MB
  95. 2. deep-neural-network/03_hyperparameter-tuning-batch-normalization-and-programming-frameworks/03_multi-class-classification/02_training-a-softmax-classifier.mp412.14MB
  96. 4. convolutional-neural-networks/01_foundations-of-convolutional-neural-networks/01_convolutional-neural-networks/11_why-convolutions.mp412.34MB
  97. 4. convolutional-neural-networks/02_deep-convolutional-models-case-studies/02_practical-advices-for-using-convnets/03_data-augmentation.mp412.43MB
  98. 1. neural-networks-deep-learning/02_neural-networks-basics/02_python-and-vectorization/04_vectorizing-logistic-regressions-gradient-output.mp412.47MB
  99. 2. deep-neural-network/02_optimization-algorithms/01_optimization-algorithms/04_understanding-exponentially-weighted-averages.mp412.49MB
  100. 1. neural-networks-deep-learning/03_shallow-neural-networks/01_shallow-neural-network/09_gradient-descent-for-neural-networks.mp412.63MB
  101. 4. convolutional-neural-networks/02_deep-convolutional-models-case-studies/01_case-studies/06_inception-network-motivation.mp412.65MB
  102. 4. convolutional-neural-networks/01_foundations-of-convolutional-neural-networks/01_convolutional-neural-networks/06_convolutions-over-volume.mp412.89MB
  103. 1. neural-networks-deep-learning/03_shallow-neural-networks/01_shallow-neural-network/03_computing-a-neural-networks-output.mp413MB
  104. 3. machine-learning-projects/02_ml-strategy-2/02_mismatched-training-and-dev-test-set/03_addressing-data-mismatch.mp413.15MB
  105. 3. machine-learning-projects/02_ml-strategy-2/04_end-to-end-deep-learning/02_whether-to-use-end-to-end-deep-learning.mp413.18MB
  106. 1. neural-networks-deep-learning/02_neural-networks-basics/01_logistic-regression-as-a-neural-network/06_more-derivative-examples.mp413.19MB
  107. 1. neural-networks-deep-learning/01_introduction-to-deep-learning/02_introduction-to-deep-learning/03_why-is-deep-learning-taking-off.mp413.22MB
  108. 4. convolutional-neural-networks/03_object-detection/01_detection-algorithms/08_anchor-boxes.mp413.47MB
  109. 1. neural-networks-deep-learning/02_neural-networks-basics/02_python-and-vectorization/05_broadcasting-in-python.mp413.48MB
  110. 1. neural-networks-deep-learning/04_deep-neural-networks/01_deep-neural-network/04_why-deep-representations.mp413.69MB
  111. 4. convolutional-neural-networks/01_foundations-of-convolutional-neural-networks/01_convolutional-neural-networks/02_edge-detection-example.mp413.91MB
  112. 1. neural-networks-deep-learning/02_neural-networks-basics/01_logistic-regression-as-a-neural-network/04_gradient-descent.mp413.94MB
  113. 3. machine-learning-projects/02_ml-strategy-2/01_error-analysis/01_carrying-out-error-analysis.mp413.96MB
  114. 1. neural-networks-deep-learning/04_deep-neural-networks/01_deep-neural-network/06_forward-and-backward-propagation.mp414MB
  115. 3. machine-learning-projects/02_ml-strategy-2/02_mismatched-training-and-dev-test-set/01_training-and-testing-on-different-distributions.mp414.3MB
  116. 1. neural-networks-deep-learning/04_deep-neural-networks/01_deep-neural-network/03_getting-your-matrix-dimensions-right.mp414.36MB
  117. 2. deep-neural-network/01_practical-aspects-of-deep-learning/01_setting-up-your-machine-learning-application/01_train-dev-test-sets.mp414.38MB
  118. 2. deep-neural-network/02_optimization-algorithms/01_optimization-algorithms/02_understanding-mini-batch-gradient-descent.mp414.41MB
  119. 4. convolutional-neural-networks/03_object-detection/01_detection-algorithms/04_convolutional-implementation-of-sliding-windows.mp414.44MB
  120. 3. machine-learning-projects/01_ml-strategy-1/01_introduction-to-ml-strategy/02_orthogonalization.mp414.46MB
  121. 3. machine-learning-projects/01_ml-strategy-1/03_comparing-to-human-level-performance/03_understanding-human-level-performance.mp414.51MB
  122. 1. neural-networks-deep-learning/03_shallow-neural-networks/01_shallow-neural-network/06_activation-functions.mp414.59MB
  123. 3. machine-learning-projects/01_ml-strategy-1/02_setting-up-your-goal/05_when-to-change-dev-test-sets-and-metrics.mp414.71MB
  124. 2. deep-neural-network/03_hyperparameter-tuning-batch-normalization-and-programming-frameworks/03_multi-class-classification/01_softmax-regression.mp414.72MB
  125. 2. deep-neural-network/02_optimization-algorithms/01_optimization-algorithms/01_mini-batch-gradient-descent.mp414.92MB
  126. 3. machine-learning-projects/02_ml-strategy-2/04_end-to-end-deep-learning/01_what-is-end-to-end-deep-learning.mp414.99MB
  127. 4. convolutional-neural-networks/03_object-detection/01_detection-algorithms/01_object-localization.mp415.36MB
  128. 4. convolutional-neural-networks/02_deep-convolutional-models-case-studies/02_practical-advices-for-using-convnets/04_state-of-computer-vision.mp415.47MB
  129. 3. machine-learning-projects/02_ml-strategy-2/03_learning-from-multiple-tasks/01_transfer-learning.mp415.55MB
  130. 4. convolutional-neural-networks/01_foundations-of-convolutional-neural-networks/01_convolutional-neural-networks/10_cnn-example.mp415.91MB
  131. 4. convolutional-neural-networks/04_special-applications-face-recognition-neural-style-transfer/02_neural-style-transfer/05_style-cost-function.mp416.36MB
  132. 2. deep-neural-network/03_hyperparameter-tuning-batch-normalization-and-programming-frameworks/02_batch-normalization/03_why-does-batch-norm-work.mp416.47MB
  133. 2. deep-neural-network/03_hyperparameter-tuning-batch-normalization-and-programming-frameworks/02_batch-normalization/02_fitting-batch-norm-into-a-neural-network.mp416.63MB
  134. 1. neural-networks-deep-learning/02_neural-networks-basics/01_logistic-regression-as-a-neural-network/08_derivatives-with-a-computation-graph.mp418.13MB
  135. 3. machine-learning-projects/02_ml-strategy-2/01_error-analysis/02_cleaning-up-incorrectly-labeled-data.mp418.3MB
  136. 3. machine-learning-projects/02_ml-strategy-2/03_learning-from-multiple-tasks/02_multi-task-learning.mp418.76MB
  137. 4. convolutional-neural-networks/03_object-detection/01_detection-algorithms/05_bounding-box-predictions.mp419.58MB
  138. 4. convolutional-neural-networks/04_special-applications-face-recognition-neural-style-transfer/01_face-recognition/04_triplet-loss.mp419.71MB
  139. 4. convolutional-neural-networks/01_foundations-of-convolutional-neural-networks/01_convolutional-neural-networks/07_one-layer-of-a-convolutional-network.mp420.06MB
  140. 1. neural-networks-deep-learning/03_shallow-neural-networks/01_shallow-neural-network/10_backpropagation-intuition-optional.mp420.31MB
  141. 2. deep-neural-network/03_hyperparameter-tuning-batch-normalization-and-programming-frameworks/04_introduction-to-programming-frameworks/02_tensorflow.mp421.34MB
  142. 3. machine-learning-projects/02_ml-strategy-2/02_mismatched-training-and-dev-test-set/02_bias-and-variance-with-mismatched-data-distributions.mp422.74MB
  143. 4. convolutional-neural-networks/02_deep-convolutional-models-case-studies/01_case-studies/02_classic-networks.mp422.75MB
  144. 1. neural-networks-deep-learning/03_shallow-neural-networks/03_heroes-of-deep-learning-optional/01_ian-goodfellow-interview.mp424.79MB
  145. 2. deep-neural-network/02_optimization-algorithms/03_heroes-of-deep-learning-optional/01_yuanqing-lin-interview.mp427.08MB
  146. 1. neural-networks-deep-learning/02_neural-networks-basics/04_heroes-of-deep-learning-optional/01_pieter-abbeel-interview.mp435.54MB
  147. 3. machine-learning-projects/01_ml-strategy-1/05_heroes-of-deep-learning-optional/01_andrej-karpathy-interview.mp436.55MB
  148. 3. machine-learning-projects/02_ml-strategy-2/05_heroes-of-deep-learning-optional/01_ruslan-salakhutdinov-interview.mp444.72MB
  149. 2. deep-neural-network/01_practical-aspects-of-deep-learning/05_heroes-of-deep-learning-optional/01_yoshua-bengio-interview.mp455.15MB
  150. 1. neural-networks-deep-learning/01_introduction-to-deep-learning/03_heroes-of-deep-learning-optional/01_geoffrey-hinton-interview.mp484.52MB
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