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[] Udemy - Convolutional Neural Networks in Python CNN Computer Vision

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文件列表

  1. 10. Python - Solving a Regression problem using ANN/1. Building Neural Network for Regression Problem.mp4 156MB
  2. 12. Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 152MB
  3. 20. Transfer Learning in Python/1. Project - Transfer Learning - VGG16.mp4 129MB
  4. 4. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4 122MB
  5. 11. Complex ANN Architectures using Functional API/1. Using Functional API for complex architectures.mp4 92MB
  6. 3. Single Cells - Perceptron and Sigmoid Neuron/3. Python - Creating Perceptron model.mp4 87MB
  7. 9. Python - Building and training the Model/3. Compiling and Training the Neural Network model.mp4 82MB
  8. 9. Python - Building and training the Model/2. Building the Neural Network using Keras.mp4 79MB
  9. 17. Project Creating CNN model from scratch/3. Project - Data Preprocessing in Python.mp4 72MB
  10. 9. Python - Building and training the Model/4. Evaluating performance and Predicting using Keras.mp4 70MB
  11. 14. CNN - Basics/5. Channels.mp4 68MB
  12. 17. Project Creating CNN model from scratch/4. Project - Training CNN model in Python.mp4 66MB
  13. 2. Setting up Python and Jupyter Notebook/3. Opening Jupyter Notebook.mp4 65MB
  14. 2. Setting up Python and Jupyter Notebook/6. Strings in Python Python Basics.mp4 64MB
  15. 5. Important concepts Common Interview questions/1. Some Important Concepts.mp4 62MB
  16. 13. Hyperparameter Tuning/1. Hyperparameter Tuning.mp4 61MB
  17. 4. Neural Networks - Stacking cells to create network/2. Gradient Descent.mp4 60MB
  18. 2. Setting up Python and Jupyter Notebook/7. Lists, Tuples and Directories Python Basics.mp4 60MB
  19. 16. Analyzing impact of Pooling layer/1. Comparison - Pooling vs Without Pooling in Python.mp4 58MB
  20. 8. Python - Dataset for classification problem/1. Dataset for classification.mp4 56MB
  21. 15. Creating CNN model in Python/3. CNN model in Python - Training and results.mp4 55MB
  22. 18. Project Data Augmentation for avoiding overfitting/2. Project - Data Augmentation Training and Results.mp4 53MB
  23. 14. CNN - Basics/4. Filters and Feature maps.mp4 53MB
  24. 14. CNN - Basics/1. CNN Introduction.mp4 51MB
  25. 17. Project Creating CNN model from scratch/1. Project - Introduction.mp4 49MB
  26. 2. Setting up Python and Jupyter Notebook/9. Working with Pandas Library of Python.mp4 47MB
  27. 14. CNN - Basics/6. PoolingLayer.mp4 47MB
  28. 6. Standard Model Parameters/1. Hyperparameters.mp4 45MB
  29. 3. Single Cells - Perceptron and Sigmoid Neuron/1. Perceptron.mp4 45MB
  30. 8. Python - Dataset for classification problem/2. Normalization and Test-Train split.mp4 44MB
  31. 2. Setting up Python and Jupyter Notebook/8. Working with Numpy Library of Python.mp4 44MB
  32. 15. Creating CNN model in Python/2. CNN model in Python - structure and Compile.mp4 43MB
  33. 18. Project Data Augmentation for avoiding overfitting/1. Project - Data Augmentation Preprocessing.mp4 41MB
  34. 2. Setting up Python and Jupyter Notebook/4. Introduction to Jupyter.mp4 41MB
  35. 15. Creating CNN model in Python/1. CNN model in Python - Preprocessing.mp4 41MB
  36. 4. Neural Networks - Stacking cells to create network/1. Basic Terminologies.mp4 40MB
  37. 2. Setting up Python and Jupyter Notebook/10. Working with Seaborn Library of Python.mp4 40MB
  38. 3. Single Cells - Perceptron and Sigmoid Neuron/2. Activation Functions.mp4 35MB
  39. 14. CNN - Basics/3. Padding.mp4 32MB
  40. 19. Transfer Learning Basics/5. Transfer Learning.mp4 30MB
  41. 1. Introduction/1. Introduction.mp4 23MB
  42. 19. Transfer Learning Basics/4. GoogLeNet.mp4 21MB
  43. 17. Project Creating CNN model from scratch/5. Project in Python - model results.mp4 21MB
  44. 19. Transfer Learning Basics/1. ILSVRC.mp4 21MB
  45. 2. Setting up Python and Jupyter Notebook/2. This is a milestone!.mp4 21MB
  46. 7. Tensorflow and Keras/2. Installing Tensorflow and Keras.mp4 20MB
  47. 14. CNN - Basics/2. Stride.mp4 17MB
  48. 2. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.mp4 16MB
  49. 7. Tensorflow and Keras/1. Keras and Tensorflow.mp4 15MB
  50. 2. Setting up Python and Jupyter Notebook/5. Arithmetic operators in Python Python Basics.mp4 13MB
  51. 21. Bonus Section/1. The final milestone!.mp4 12MB
  52. 9. Python - Building and training the Model/1. Different ways to create ANN using Keras.mp4 11MB
  53. 19. Transfer Learning Basics/3. VGG16NET.mp4 10MB
  54. 19. Transfer Learning Basics/2. LeNET.mp4 7MB
  55. 4. Neural Networks - Stacking cells to create network/3. Back Propagation.srt 23KB
  56. 10. Python - Solving a Regression problem using ANN/1. Building Neural Network for Regression Problem.srt 22KB
  57. 20. Transfer Learning in Python/1. Project - Transfer Learning - VGG16.srt 19KB
  58. 12. Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.srt 19KB
  59. 2. Setting up Python and Jupyter Notebook/7. Lists, Tuples and Directories Python Basics.srt 17KB
  60. 2. Setting up Python and Jupyter Notebook/6. Strings in Python Python Basics.srt 16KB
  61. 3. Single Cells - Perceptron and Sigmoid Neuron/3. Python - Creating Perceptron model.srt 15KB
  62. 5. Important concepts Common Interview questions/1. Some Important Concepts.srt 13KB
  63. 2. Setting up Python and Jupyter Notebook/4. Introduction to Jupyter.srt 12KB
  64. 9. Python - Building and training the Model/2. Building the Neural Network using Keras.srt 12KB
  65. 4. Neural Networks - Stacking cells to create network/2. Gradient Descent.srt 12KB
  66. 11. Complex ANN Architectures using Functional API/1. Using Functional API for complex architectures.srt 12KB
  67. 2. Setting up Python and Jupyter Notebook/8. Working with Numpy Library of Python.srt 10KB
  68. 3. Single Cells - Perceptron and Sigmoid Neuron/1. Perceptron.srt 10KB
  69. 9. Python - Building and training the Model/3. Compiling and Training the Neural Network model.srt 10KB
  70. 4. Neural Networks - Stacking cells to create network/1. Basic Terminologies.srt 10KB
  71. 13. Hyperparameter Tuning/1. Hyperparameter Tuning.srt 9KB
  72. 2. Setting up Python and Jupyter Notebook/3. Opening Jupyter Notebook.srt 9KB
  73. 9. Python - Building and training the Model/4. Evaluating performance and Predicting using Keras.srt 9KB
  74. 6. Standard Model Parameters/1. Hyperparameters.srt 9KB
  75. 17. Project Creating CNN model from scratch/4. Project - Training CNN model in Python.srt 9KB
  76. 17. Project Creating CNN model from scratch/3. Project - Data Preprocessing in Python.srt 9KB
  77. 2. Setting up Python and Jupyter Notebook/9. Working with Pandas Library of Python.srt 8KB
  78. 3. Single Cells - Perceptron and Sigmoid Neuron/2. Activation Functions.srt 8KB
  79. 14. CNN - Basics/1. CNN Introduction.srt 8KB
  80. 2. Setting up Python and Jupyter Notebook/10. Working with Seaborn Library of Python.srt 8KB
  81. 8. Python - Dataset for classification problem/1. Dataset for classification.srt 7KB
  82. 17. Project Creating CNN model from scratch/1. Project - Introduction.srt 7KB
  83. 18. Project Data Augmentation for avoiding overfitting/1. Project - Data Augmentation Preprocessing.srt 7KB
  84. 15. Creating CNN model in Python/2. CNN model in Python - structure and Compile.srt 7KB
  85. 14. CNN - Basics/4. Filters and Feature maps.srt 7KB
  86. 18. Project Data Augmentation for avoiding overfitting/2. Project - Data Augmentation Training and Results.srt 6KB
  87. 15. Creating CNN model in Python/3. CNN model in Python - Training and results.srt 6KB
  88. 14. CNN - Basics/5. Channels.srt 6KB
  89. 8. Python - Dataset for classification problem/2. Normalization and Test-Train split.srt 6KB
  90. 15. Creating CNN model in Python/1. CNN model in Python - Preprocessing.srt 6KB
  91. 19. Transfer Learning Basics/5. Transfer Learning.srt 5KB
  92. 16. Analyzing impact of Pooling layer/1. Comparison - Pooling vs Without Pooling in Python.srt 5KB
  93. 14. CNN - Basics/6. PoolingLayer.srt 5KB
  94. 14. CNN - Basics/3. Padding.srt 5KB
  95. 19. Transfer Learning Basics/1. ILSVRC.srt 4KB
  96. 2. Setting up Python and Jupyter Notebook/5. Arithmetic operators in Python Python Basics.srt 4KB
  97. 7. Tensorflow and Keras/2. Installing Tensorflow and Keras.srt 4KB
  98. 2. Setting up Python and Jupyter Notebook/2. This is a milestone!.srt 4KB
  99. 1. Introduction/1. Introduction.srt 4KB
  100. 7. Tensorflow and Keras/1. Keras and Tensorflow.srt 4KB
  101. 19. Transfer Learning Basics/4. GoogLeNet.srt 3KB
  102. 14. CNN - Basics/2. Stride.srt 3KB
  103. 17. Project Creating CNN model from scratch/5. Project in Python - model results.srt 3KB
  104. 2. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.srt 3KB
  105. 9. Python - Building and training the Model/1. Different ways to create ANN using Keras.srt 2KB
  106. 19. Transfer Learning Basics/3. VGG16NET.srt 2KB
  107. 21. Bonus Section/1. The final milestone!.srt 2KB
  108. 19. Transfer Learning Basics/2. LeNET.srt 2KB
  109. 21. Bonus Section/2. Congratulations & About your certificate.html 2KB
  110. 8. Python - Dataset for classification problem/3. More about test-train split.html 559B
  111. 1. Introduction/2. Course Resources.html 335B
  112. 17. Project Creating CNN model from scratch/2. Data for the project.html 232B
  113. 14. CNN - Basics/7. Quiz.html 210B
  114. 4. Neural Networks - Stacking cells to create network/4. Quiz.html 210B
  115. 5. Important concepts Common Interview questions/2. Quiz.html 210B
  116. 6. Standard Model Parameters/2. Quiz.html 210B
  117. 0. Websites you may like/[FCS Forum].url 133B
  118. 0. Websites you may like/[FreeCourseSite.com].url 127B
  119. 17. Project Creating CNN model from scratch/2.1 Dataset.html 127B
  120. 0. Websites you may like/[CourseClub.ME].url 122B
  121. 0. Websites you may like/[GigaCourse.Com].url 49B