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[] Udemy - CNN for Computer Vision with Keras and TensorFlow in R

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  • 文件大小:3GB
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文件列表

  1. 11. Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 216MB
  2. 9. R - Building and training the Model/1. Building, Compiling and Training.mp4 131MB
  3. 4. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4 122MB
  4. 8. R - Dataset for classification problem/1. Data Normalization and Test-Train Split.mp4 112MB
  5. 19. Transfer Learning in R/1. Project - Transfer Learning - VGG16 (Implementation).mp4 102MB
  6. 9. R - Building and training the Model/2. Evaluating and Predicting.mp4 99MB
  7. 2. Setting Up R Studio and R crash course/7. Creating Barplots in R.mp4 97MB
  8. 16. Project Creating CNN model from scratch/3. Project in R - Data Preprocessing.mp4 88MB
  9. 10. The NeuralNets Package/1. ANN with NeuralNets Package.mp4 84MB
  10. 2. Setting Up R Studio and R crash course/3. Packages in R.mp4 83MB
  11. 14. Creating CNN model in R/3. Creating Model Architecture.mp4 72MB
  12. 14. Creating CNN model in R/5. Model Performance.mp4 68MB
  13. 13. CNN - Basics/5. Channels.mp4 68MB
  14. 14. Creating CNN model in R/2. Data Preprocessing.mp4 67MB
  15. 19. Transfer Learning in R/2. Project - Transfer Learning - VGG16 (Performance).mp4 64MB
  16. 5. Important concepts Common Interview questions/1. Some Important Concepts.mp4 62MB
  17. 12. Hyperparameter Tuning/1. Hyperparameter Tuning.mp4 61MB
  18. 4. Neural Networks - Stacking cells to create network/2. Gradient Descent.mp4 60MB
  19. 2. Setting Up R Studio and R crash course/6. Inputting data part 3 Importing from CSV or Text files.mp4 60MB
  20. 17. Project Data Augmentation for avoiding overfitting/1. Project in R - Data Augmentation.mp4 56MB
  21. 13. CNN - Basics/4. Filters and Feature maps.mp4 53MB
  22. 13. CNN - Basics/1. CNN Introduction.mp4 51MB
  23. 16. Project Creating CNN model from scratch/1. Project - Introduction.mp4 49MB
  24. 13. CNN - Basics/6. PoolingLayer.mp4 47MB
  25. 16. Project Creating CNN model from scratch/4. CNN Project in R - Structure and Compile.mp4 46MB
  26. 6. Standard Model Parameters/1. Hyperparameters.mp4 45MB
  27. 3. Single Cells - Perceptron and Sigmoid Neuron/1. Perceptron.mp4 45MB
  28. 15. Analyzing impact of Pooling layer/1. Comparison - Pooling vs Without Pooling in R.mp4 45MB
  29. 2. Setting Up R Studio and R crash course/8. Creating Histograms in R.mp4 42MB
  30. 2. Setting Up R Studio and R crash course/4. Inputting data part 1 Inbuilt datasets of R.mp4 41MB
  31. 4. Neural Networks - Stacking cells to create network/1. Basic Terminologies.mp4 40MB
  32. 2. Setting Up R Studio and R crash course/2. Basics of R and R studio.mp4 39MB
  33. 2. Setting Up R Studio and R crash course/1. Installing R and R studio.mp4 36MB
  34. 3. Single Cells - Perceptron and Sigmoid Neuron/2. Activation Functions.mp4 35MB
  35. 14. Creating CNN model in R/4. Compiling and training.mp4 32MB
  36. 13. CNN - Basics/3. Padding.mp4 32MB
  37. 18. Transfer Learning Basics/5. Transfer Learning.mp4 30MB
  38. 2. Setting Up R Studio and R crash course/5. Inputting data part 2 Manual data entry.mp4 26MB
  39. 16. Project Creating CNN model from scratch/5. Project in R - Training.mp4 25MB
  40. 17. Project Data Augmentation for avoiding overfitting/2. Project in R - Validation Performance.mp4 24MB
  41. 16. Project Creating CNN model from scratch/6. Project in R - Model Performance.mp4 23MB
  42. 7. Tensorflow and Keras/2. Installing Keras and Tensorflow.mp4 23MB
  43. 1. Introduction/1. Introduction.mp4 22MB
  44. 18. Transfer Learning Basics/4. GoogLeNet.mp4 21MB
  45. 18. Transfer Learning Basics/1. ILSVRC.mp4 21MB
  46. 13. CNN - Basics/2. Stride.mp4 17MB
  47. 7. Tensorflow and Keras/1. Keras and Tensorflow.mp4 15MB
  48. 2. Setting Up R Studio and R crash course/3. Packages in R.srt 14MB
  49. 18. Transfer Learning Basics/3. VGG16NET.mp4 10MB
  50. 1. Introduction/2.1 ST Academy - CNN course files R.zip 8MB
  51. 14. Creating CNN model in R/1. CNN on MNIST Fashion Dataset - Model Architecture.mp4 7MB
  52. 18. Transfer Learning Basics/2. LeNET.mp4 7MB
  53. 4. Neural Networks - Stacking cells to create network/3. Back Propagation.srt 23KB
  54. 11. Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.srt 20KB
  55. 9. R - Building and training the Model/1. Building, Compiling and Training.srt 15KB
  56. 2. Setting Up R Studio and R crash course/7. Creating Barplots in R.srt 13KB
  57. 19. Transfer Learning in R/1. Project - Transfer Learning - VGG16 (Implementation).srt 13KB
  58. 5. Important concepts Common Interview questions/1. Some Important Concepts.srt 13KB
  59. 8. R - Dataset for classification problem/1. Data Normalization and Test-Train Split.srt 12KB
  60. 4. Neural Networks - Stacking cells to create network/2. Gradient Descent.srt 12KB
  61. 16. Project Creating CNN model from scratch/3. Project in R - Data Preprocessing.srt 11KB
  62. 2. Setting Up R Studio and R crash course/2. Basics of R and R studio.srt 11KB
  63. 3. Single Cells - Perceptron and Sigmoid Neuron/1. Perceptron.srt 10KB
  64. 4. Neural Networks - Stacking cells to create network/1. Basic Terminologies.srt 10KB
  65. 12. Hyperparameter Tuning/1. Hyperparameter Tuning.srt 9KB
  66. 9. R - Building and training the Model/2. Evaluating and Predicting.srt 9KB
  67. 6. Standard Model Parameters/1. Hyperparameters.srt 9KB
  68. 19. Transfer Learning in R/2. Project - Transfer Learning - VGG16 (Performance).srt 8KB
  69. 3. Single Cells - Perceptron and Sigmoid Neuron/2. Activation Functions.srt 8KB
  70. 10. The NeuralNets Package/1. ANN with NeuralNets Package.srt 8KB
  71. 17. Project Data Augmentation for avoiding overfitting/1. Project in R - Data Augmentation.srt 7KB
  72. 14. Creating CNN model in R/2. Data Preprocessing.srt 7KB
  73. 16. Project Creating CNN model from scratch/1. Project - Introduction.srt 7KB
  74. 13. CNN - Basics/4. Filters and Feature maps.srt 7KB
  75. 2. Setting Up R Studio and R crash course/6. Inputting data part 3 Importing from CSV or Text files.srt 6KB
  76. 14. Creating CNN model in R/5. Model Performance.srt 6KB
  77. 14. Creating CNN model in R/3. Creating Model Architecture.srt 6KB
  78. 2. Setting Up R Studio and R crash course/8. Creating Histograms in R.srt 6KB
  79. 13. CNN - Basics/5. Channels.srt 6KB
  80. 2. Setting Up R Studio and R crash course/1. Installing R and R studio.srt 6KB
  81. 18. Transfer Learning Basics/5. Transfer Learning.srt 5KB
  82. 16. Project Creating CNN model from scratch/4. CNN Project in R - Structure and Compile.srt 5KB
  83. 13. CNN - Basics/6. PoolingLayer.srt 5KB
  84. 13. CNN - Basics/3. Padding.srt 5KB
  85. 18. Transfer Learning Basics/1. ILSVRC.srt 4KB
  86. 15. Analyzing impact of Pooling layer/1. Comparison - Pooling vs Without Pooling in R.srt 4KB
  87. 2. Setting Up R Studio and R crash course/4. Inputting data part 1 Inbuilt datasets of R.srt 4KB
  88. 1. Introduction/1. Introduction.srt 4KB
  89. 7. Tensorflow and Keras/1. Keras and Tensorflow.srt 4KB
  90. 14. Creating CNN model in R/4. Compiling and training.srt 3KB
  91. 18. Transfer Learning Basics/4. GoogLeNet.srt 3KB
  92. 7. Tensorflow and Keras/2. Installing Keras and Tensorflow.srt 3KB
  93. 2. Setting Up R Studio and R crash course/5. Inputting data part 2 Manual data entry.srt 3KB
  94. 16. Project Creating CNN model from scratch/5. Project in R - Training.srt 3KB
  95. 13. CNN - Basics/2. Stride.srt 3KB
  96. 17. Project Data Augmentation for avoiding overfitting/2. Project in R - Validation Performance.srt 3KB
  97. 16. Project Creating CNN model from scratch/6. Project in R - Model Performance.srt 3KB
  98. 18. Transfer Learning Basics/3. VGG16NET.srt 2KB
  99. 18. Transfer Learning Basics/2. LeNET.srt 2KB
  100. Readme.txt 962B
  101. 16. Project Creating CNN model from scratch/2. Data for the project.html 232B
  102. 4. Neural Networks - Stacking cells to create network/4. Quiz.html 165B
  103. 5. Important concepts Common Interview questions/2. Quiz.html 165B
  104. 16. Project Creating CNN model from scratch/2.1 Download the project dataset.html 127B
  105. 1. Introduction/2. Course resources.html 82B
  106. [GigaCourse.com].url 49B
  107. 14. Creating CNN model in R/1. CNN on MNIST Fashion Dataset - Model Architecture.srt 0B