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[FreeCourseLab.com] Udemy - Artificial Intelligence II - Neural Networks in Java

FreeCourseLabUdemyArtificialIntelligenceNeuralNetworksJava

种子大小：818.26 Mb

收录时间：2026-04-02

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文件列表：

  1. 2. Neural Networks Introduction/2. Modeling human brain.mp493.92 Mb
  2. 11. Optical Character Recognition (OCR)/5. OCR with neural network.mp443.94 Mb
  3. 10. Classification - Iris Dataset/3. Testing the neural network.mp434.16 Mb
  4. 4. Neural Networks With Backpropagation Theory/2. Optimization - cost function.mp425.89 Mb
  5. 4. Neural Networks With Backpropagation Theory/8. Gradient calculation I - output layer.mp420.27 Mb
  6. 4. Neural Networks With Backpropagation Theory/4. Simplified feedforward network.mp419.42 Mb
  7. 2. Neural Networks Introduction/1. Axons and neurons in the human brain.mp419.29 Mb
  8. 3. Hopfield Neural Network/7. Hopfield network implementation II - matrix operations.mp419.06 Mb
  9. 3. Hopfield Neural Network/8. Hopfield network implementation III - network.mp418.62 Mb
  10. 4. Neural Networks With Backpropagation Theory/13. Resilient propagation.mp418.56 Mb
  11. 4. Neural Networks With Backpropagation Theory/1. Feedforward neural networks.mp418.41 Mb
  12. 7. Backpropagation Implementation/3. Backpropagation implementation II - NeuralNetwork.mp418.3 Mb
  13. 8. Logical Operators/2. Running the neural network AND.mp417.96 Mb
  14. 2. Neural Networks Introduction/4. Artificial neurons - the model.mp416.55 Mb
  15. 7. Backpropagation Implementation/5. Backpropagation implementation IV - run.mp416.42 Mb
  16. 7. Backpropagation Implementation/6. Backpropagation implementation V - train.mp416.02 Mb
  17. 4. Neural Networks With Backpropagation Theory/5. Feedforward neural network topology.mp414.72 Mb
  18. 2. Neural Networks Introduction/5. Artificial neurons - activations functions.mp414.25 Mb
  19. 4. Neural Networks With Backpropagation Theory/7. Error calculation.mp413.73 Mb
  20. 6. Single Perceptron Model/4. Perceptron model implementation III.mp413.67 Mb
  21. 9. Clustering/2. Clustering with neural networks II.mp413.49 Mb
  22. 4. Neural Networks With Backpropagation Theory/6. The learning algorithm.mp413.25 Mb
  23. 3. Hopfield Neural Network/5. Hopfield neural network example.mp413.17 Mb
  24. 7. Backpropagation Implementation/1. Structure of the feedforward network.mp413.12 Mb
  25. 6. Single Perceptron Model/3. Perceptron model implementation II.mp412.83 Mb
  26. 4. Neural Networks With Backpropagation Theory/10. Backpropagation.mp412.67 Mb
  27. 7. Backpropagation Implementation/4. Backpropagation implementation III - Layer.mp412.07 Mb
  28. 3. Hopfield Neural Network/1. Hopfield neural network introduction.mp411.76 Mb
  29. 3. Hopfield Neural Network/3. Hopfield neural network training and learning.mp411.55 Mb
  30. 6. Single Perceptron Model/2. Perceptron model implementation I.mp411.54 Mb
  31. 2. Neural Networks Introduction/7. Artificial neurons - an example.mp411.37 Mb
  32. 2. Neural Networks Introduction/8. Neural networks - the big picture.mp410.77 Mb
  33. 7. Backpropagation Implementation/2. Backpropagation implementation I - activation function.mp49.85 Mb
  34. 11. Optical Character Recognition (OCR)/3. Transform an image into numerical data.mp49.83 Mb
  35. 4. Neural Networks With Backpropagation Theory/15. Applications of neural networks II - stock market forecast.mp49.52 Mb
  36. 4. Neural Networks With Backpropagation Theory/16. Deep learning.mp49.46 Mb
  37. 3. Hopfield Neural Network/6. Hopfield network implementation I - utils.mp49.39 Mb
  38. 3. Hopfield Neural Network/2. Hopfield network energy.mp49.35 Mb
  39. 4. Neural Networks With Backpropagation Theory/9. Gradient calculation II - hidden layer.mp49.17 Mb
  40. 4. Neural Networks With Backpropagation Theory/14. Applications of neural networks I - character recognition.mp48.77 Mb
  41. 3. Hopfield Neural Network/9. Hopfield network implementation IV - running the application.mp48.77 Mb
  42. 8. Logical Operators/3. Running the neural network OR.mp48.06 Mb
  43. 10. Classification - Iris Dataset/2. Constructing the neural network.mp48.03 Mb
  44. 11. Optical Character Recognition (OCR)/1. Optical character recognition theory.mp47.88 Mb
  45. 11. Optical Character Recognition (OCR)/4. Creating the datasets.mp47.64 Mb
  46. 3. Hopfield Neural Network/4. Hopfield neural network problems.mp47.19 Mb
  47. 10. Classification - Iris Dataset/1. About the Iris dataset.mp47.12 Mb
  48. 1. Introduction/1. Introduction.mp46.95 Mb
  49. 2. Neural Networks Introduction/3. Learning paradigms.mp46.86 Mb
  50. 6. Single Perceptron Model/6. Conclusion linearity and hidden layers.mp46.73 Mb
  51. 8. Logical Operators/4. Running the neural network XOR.mp45.56 Mb
  52. 5. Types of Neural Networks/1. Types of neural networks.mp45.48 Mb
  53. 2. Neural Networks Introduction/9. Applications of neural networks.mp45.23 Mb
  54. 11. Optical Character Recognition (OCR)/2. Installing paint.net.mp45.15 Mb
  55. 9. Clustering/1. Clustering with neural networks I.mp44.76 Mb
  56. 6. Single Perceptron Model/1. Perceptron model training.mp44.67 Mb
  57. 4. Neural Networks With Backpropagation Theory/11. Backpropagation II.mp44.67 Mb
  58. 8. Logical Operators/1. Logical operators introduction.mp44.62 Mb
  59. 6. Single Perceptron Model/5. Trying to solve XOR problem.mp44.5 Mb
  60. 12. Course Materials (DOWNLOADS)/1.1 neural_networks.zip.zip2.02 Mb
  61. 4. Neural Networks With Backpropagation Theory/2. Optimization - cost function.vtt11.85 Kb
  62. 4. Neural Networks With Backpropagation Theory/8. Gradient calculation I - output layer.vtt9.29 Kb
  63. 2. Neural Networks Introduction/1. Axons and neurons in the human brain.vtt9.2 Kb
  64. 4. Neural Networks With Backpropagation Theory/4. Simplified feedforward network.vtt9.03 Kb
  65. 4. Neural Networks With Backpropagation Theory/1. Feedforward neural networks.vtt8.88 Kb
  66. 2. Neural Networks Introduction/2. Modeling human brain.vtt8.31 Kb
  67. 7. Backpropagation Implementation/3. Backpropagation implementation II - NeuralNetwork.vtt7.83 Kb
  68. 8. Logical Operators/2. Running the neural network AND.vtt7.65 Kb
  69. 2. Neural Networks Introduction/4. Artificial neurons - the model.vtt7.41 Kb
  70. 3. Hopfield Neural Network/7. Hopfield network implementation II - matrix operations.vtt7.3 Kb
  71. 3. Hopfield Neural Network/8. Hopfield network implementation III - network.vtt7.18 Kb
  72. 7. Backpropagation Implementation/5. Backpropagation implementation IV - run.vtt7.07 Kb
  73. 10. Classification - Iris Dataset/3. Testing the neural network.vtt6.83 Kb
  74. 7. Backpropagation Implementation/6. Backpropagation implementation V - train.vtt6.75 Kb
  75. 11. Optical Character Recognition (OCR)/5. OCR with neural network.vtt6.71 Kb
  76. 7. Backpropagation Implementation/1. Structure of the feedforward network.vtt6.68 Kb
  77. 4. Neural Networks With Backpropagation Theory/5. Feedforward neural network topology.vtt6.56 Kb
  78. 2. Neural Networks Introduction/5. Artificial neurons - activations functions.vtt6.55 Kb
  79. 4. Neural Networks With Backpropagation Theory/7. Error calculation.vtt6.51 Kb
  80. 3. Hopfield Neural Network/5. Hopfield neural network example.vtt6.26 Kb
  81. 4. Neural Networks With Backpropagation Theory/6. The learning algorithm.vtt6.03 Kb
  82. 4. Neural Networks With Backpropagation Theory/10. Backpropagation.vtt5.72 Kb
  83. 6. Single Perceptron Model/4. Perceptron model implementation III.vtt5.71 Kb
  84. 6. Single Perceptron Model/3. Perceptron model implementation II.vtt5.64 Kb
  85. 3. Hopfield Neural Network/3. Hopfield neural network training and learning.vtt5.61 Kb
  86. 3. Hopfield Neural Network/1. Hopfield neural network introduction.vtt5.54 Kb
  87. 9. Clustering/2. Clustering with neural networks II.vtt5.19 Kb
  88. 4. Neural Networks With Backpropagation Theory/13. Resilient propagation.vtt5.06 Kb
  89. 13. DISCOUNT FOR OTHER COURSES!/1. 90% OFF For Other Courses.html5.05 Kb
  90. 7. Backpropagation Implementation/4. Backpropagation implementation III - Layer.vtt4.87 Kb
  91. 2. Neural Networks Introduction/8. Neural networks - the big picture.vtt4.83 Kb
  92. 6. Single Perceptron Model/2. Perceptron model implementation I.vtt4.82 Kb
  93. 2. Neural Networks Introduction/7. Artificial neurons - an example.vtt4.81 Kb
  94. 11. Optical Character Recognition (OCR)/3. Transform an image into numerical data.vtt4.75 Kb
  95. 4. Neural Networks With Backpropagation Theory/15. Applications of neural networks II - stock market forecast.vtt4.69 Kb
  96. 4. Neural Networks With Backpropagation Theory/16. Deep learning.vtt4.58 Kb
  97. 7. Backpropagation Implementation/2. Backpropagation implementation I - activation function.vtt4.53 Kb
  98. 3. Hopfield Neural Network/2. Hopfield network energy.vtt4.49 Kb
  99. 4. Neural Networks With Backpropagation Theory/14. Applications of neural networks I - character recognition.vtt4.43 Kb
  100. 5. Types of Neural Networks/1. Types of neural networks.vtt4.37 Kb
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