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[] Udemy - Artificial Intelligence II - Neural Networks in Java

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文件列表

  1. 2. Neural Networks Introduction/2. Modeling human brain.mp4 94MB
  2. 11. Optical Character Recognition (OCR)/5. OCR with neural network.mp4 44MB
  3. 10. Classification - Iris Dataset/3. Testing the neural network.mp4 34MB
  4. 4. Neural Networks With Backpropagation Theory/2. Optimization - cost function.mp4 26MB
  5. 4. Neural Networks With Backpropagation Theory/8. Gradient calculation I - output layer.mp4 20MB
  6. 4. Neural Networks With Backpropagation Theory/4. Simplified feedforward network.mp4 19MB
  7. 2. Neural Networks Introduction/1. Axons and neurons in the human brain.mp4 19MB
  8. 3. Hopfield Neural Network/7. Hopfield network implementation II - matrix operations.mp4 19MB
  9. 3. Hopfield Neural Network/8. Hopfield network implementation III - network.mp4 19MB
  10. 4. Neural Networks With Backpropagation Theory/13. Resilient propagation.mp4 19MB
  11. 4. Neural Networks With Backpropagation Theory/1. Feedforward neural networks.mp4 18MB
  12. 7. Backpropagation Implementation/3. Backpropagation implementation II - NeuralNetwork.mp4 18MB
  13. 8. Logical Operators/2. Running the neural network AND.mp4 18MB
  14. 2. Neural Networks Introduction/4. Artificial neurons - the model.mp4 17MB
  15. 7. Backpropagation Implementation/5. Backpropagation implementation IV - run.mp4 16MB
  16. 7. Backpropagation Implementation/6. Backpropagation implementation V - train.mp4 16MB
  17. 4. Neural Networks With Backpropagation Theory/5. Feedforward neural network topology.mp4 15MB
  18. 2. Neural Networks Introduction/5. Artificial neurons - activations functions.mp4 14MB
  19. 4. Neural Networks With Backpropagation Theory/7. Error calculation.mp4 14MB
  20. 6. Single Perceptron Model/4. Perceptron model implementation III.mp4 14MB
  21. 9. Clustering/2. Clustering with neural networks II.mp4 13MB
  22. 4. Neural Networks With Backpropagation Theory/6. The learning algorithm.mp4 13MB
  23. 3. Hopfield Neural Network/5. Hopfield neural network example.mp4 13MB
  24. 7. Backpropagation Implementation/1. Structure of the feedforward network.mp4 13MB
  25. 6. Single Perceptron Model/3. Perceptron model implementation II.mp4 13MB
  26. 4. Neural Networks With Backpropagation Theory/10. Backpropagation.mp4 13MB
  27. 7. Backpropagation Implementation/4. Backpropagation implementation III - Layer.mp4 12MB
  28. 3. Hopfield Neural Network/1. Hopfield neural network introduction.mp4 12MB
  29. 3. Hopfield Neural Network/3. Hopfield neural network training and learning.mp4 12MB
  30. 6. Single Perceptron Model/2. Perceptron model implementation I.mp4 12MB
  31. 2. Neural Networks Introduction/7. Artificial neurons - an example.mp4 11MB
  32. 2. Neural Networks Introduction/8. Neural networks - the big picture.mp4 11MB
  33. 7. Backpropagation Implementation/2. Backpropagation implementation I - activation function.mp4 10MB
  34. 11. Optical Character Recognition (OCR)/3. Transform an image into numerical data.mp4 10MB
  35. 4. Neural Networks With Backpropagation Theory/15. Applications of neural networks II - stock market forecast.mp4 10MB
  36. 4. Neural Networks With Backpropagation Theory/16. Deep learning.mp4 9MB
  37. 3. Hopfield Neural Network/6. Hopfield network implementation I - utils.mp4 9MB
  38. 3. Hopfield Neural Network/2. Hopfield network energy.mp4 9MB
  39. 4. Neural Networks With Backpropagation Theory/9. Gradient calculation II - hidden layer.mp4 9MB
  40. 4. Neural Networks With Backpropagation Theory/14. Applications of neural networks I - character recognition.mp4 9MB
  41. 3. Hopfield Neural Network/9. Hopfield network implementation IV - running the application.mp4 9MB
  42. 8. Logical Operators/3. Running the neural network OR.mp4 8MB
  43. 10. Classification - Iris Dataset/2. Constructing the neural network.mp4 8MB
  44. 11. Optical Character Recognition (OCR)/1. Optical character recognition theory.mp4 8MB
  45. 11. Optical Character Recognition (OCR)/4. Creating the datasets.mp4 8MB
  46. 3. Hopfield Neural Network/4. Hopfield neural network problems.mp4 7MB
  47. 10. Classification - Iris Dataset/1. About the Iris dataset.mp4 7MB
  48. 1. Introduction/1. Introduction.mp4 7MB
  49. 2. Neural Networks Introduction/3. Learning paradigms.mp4 7MB
  50. 6. Single Perceptron Model/6. Conclusion linearity and hidden layers.mp4 7MB
  51. 8. Logical Operators/4. Running the neural network XOR.mp4 6MB
  52. 5. Types of Neural Networks/1. Types of neural networks.mp4 5MB
  53. 2. Neural Networks Introduction/9. Applications of neural networks.mp4 5MB
  54. 11. Optical Character Recognition (OCR)/2. Installing paint.net.mp4 5MB
  55. 9. Clustering/1. Clustering with neural networks I.mp4 5MB
  56. 6. Single Perceptron Model/1. Perceptron model training.mp4 5MB
  57. 4. Neural Networks With Backpropagation Theory/11. Backpropagation II.mp4 5MB
  58. 8. Logical Operators/1. Logical operators introduction.mp4 5MB
  59. 6. Single Perceptron Model/5. Trying to solve XOR problem.mp4 5MB
  60. 12. Course Materials (DOWNLOADS)/1.1 neural_networks.zip.zip 2MB
  61. 4. Neural Networks With Backpropagation Theory/2. Optimization - cost function.vtt 12KB
  62. 4. Neural Networks With Backpropagation Theory/8. Gradient calculation I - output layer.vtt 9KB
  63. 2. Neural Networks Introduction/1. Axons and neurons in the human brain.vtt 9KB
  64. 4. Neural Networks With Backpropagation Theory/4. Simplified feedforward network.vtt 9KB
  65. 4. Neural Networks With Backpropagation Theory/1. Feedforward neural networks.vtt 9KB
  66. 2. Neural Networks Introduction/2. Modeling human brain.vtt 8KB
  67. 7. Backpropagation Implementation/3. Backpropagation implementation II - NeuralNetwork.vtt 8KB
  68. 8. Logical Operators/2. Running the neural network AND.vtt 8KB
  69. 2. Neural Networks Introduction/4. Artificial neurons - the model.vtt 7KB
  70. 3. Hopfield Neural Network/7. Hopfield network implementation II - matrix operations.vtt 7KB
  71. 3. Hopfield Neural Network/8. Hopfield network implementation III - network.vtt 7KB
  72. 7. Backpropagation Implementation/5. Backpropagation implementation IV - run.vtt 7KB
  73. 10. Classification - Iris Dataset/3. Testing the neural network.vtt 7KB
  74. 7. Backpropagation Implementation/6. Backpropagation implementation V - train.vtt 7KB
  75. 11. Optical Character Recognition (OCR)/5. OCR with neural network.vtt 7KB
  76. 7. Backpropagation Implementation/1. Structure of the feedforward network.vtt 7KB
  77. 4. Neural Networks With Backpropagation Theory/5. Feedforward neural network topology.vtt 7KB
  78. 2. Neural Networks Introduction/5. Artificial neurons - activations functions.vtt 7KB
  79. 4. Neural Networks With Backpropagation Theory/7. Error calculation.vtt 7KB
  80. 3. Hopfield Neural Network/5. Hopfield neural network example.vtt 6KB
  81. 4. Neural Networks With Backpropagation Theory/6. The learning algorithm.vtt 6KB
  82. 4. Neural Networks With Backpropagation Theory/10. Backpropagation.vtt 6KB
  83. 6. Single Perceptron Model/4. Perceptron model implementation III.vtt 6KB
  84. 6. Single Perceptron Model/3. Perceptron model implementation II.vtt 6KB
  85. 3. Hopfield Neural Network/3. Hopfield neural network training and learning.vtt 6KB
  86. 3. Hopfield Neural Network/1. Hopfield neural network introduction.vtt 6KB
  87. 9. Clustering/2. Clustering with neural networks II.vtt 5KB
  88. 4. Neural Networks With Backpropagation Theory/13. Resilient propagation.vtt 5KB
  89. 13. DISCOUNT FOR OTHER COURSES!/1. 90% OFF For Other Courses.html 5KB
  90. 7. Backpropagation Implementation/4. Backpropagation implementation III - Layer.vtt 5KB
  91. 2. Neural Networks Introduction/8. Neural networks - the big picture.vtt 5KB
  92. 6. Single Perceptron Model/2. Perceptron model implementation I.vtt 5KB
  93. 2. Neural Networks Introduction/7. Artificial neurons - an example.vtt 5KB
  94. 11. Optical Character Recognition (OCR)/3. Transform an image into numerical data.vtt 5KB
  95. 4. Neural Networks With Backpropagation Theory/15. Applications of neural networks II - stock market forecast.vtt 5KB
  96. 4. Neural Networks With Backpropagation Theory/16. Deep learning.vtt 5KB
  97. 7. Backpropagation Implementation/2. Backpropagation implementation I - activation function.vtt 5KB
  98. 3. Hopfield Neural Network/2. Hopfield network energy.vtt 4KB
  99. 4. Neural Networks With Backpropagation Theory/14. Applications of neural networks I - character recognition.vtt 4KB
  100. 5. Types of Neural Networks/1. Types of neural networks.vtt 4KB
  101. 3. Hopfield Neural Network/9. Hopfield network implementation IV - running the application.vtt 4KB
  102. 4. Neural Networks With Backpropagation Theory/9. Gradient calculation II - hidden layer.vtt 4KB
  103. 3. Hopfield Neural Network/6. Hopfield network implementation I - utils.vtt 4KB
  104. 11. Optical Character Recognition (OCR)/1. Optical character recognition theory.vtt 4KB
  105. 8. Logical Operators/3. Running the neural network OR.vtt 4KB
  106. 1. Introduction/1. Introduction.vtt 4KB
  107. 3. Hopfield Neural Network/4. Hopfield neural network problems.vtt 4KB
  108. 6. Single Perceptron Model/6. Conclusion linearity and hidden layers.vtt 3KB
  109. 2. Neural Networks Introduction/3. Learning paradigms.vtt 3KB
  110. 10. Classification - Iris Dataset/1. About the Iris dataset.vtt 3KB
  111. 10. Classification - Iris Dataset/2. Constructing the neural network.vtt 3KB
  112. 11. Optical Character Recognition (OCR)/2. Installing paint.net.vtt 3KB
  113. 8. Logical Operators/4. Running the neural network XOR.vtt 3KB
  114. 9. Clustering/1. Clustering with neural networks I.vtt 2KB
  115. 2. Neural Networks Introduction/9. Applications of neural networks.vtt 2KB
  116. 11. Optical Character Recognition (OCR)/4. Creating the datasets.vtt 2KB
  117. 6. Single Perceptron Model/1. Perceptron model training.vtt 2KB
  118. 8. Logical Operators/1. Logical operators introduction.vtt 2KB
  119. 4. Neural Networks With Backpropagation Theory/11. Backpropagation II.vtt 2KB
  120. 6. Single Perceptron Model/5. Trying to solve XOR problem.vtt 2KB
  121. 4. Neural Networks With Backpropagation Theory/3. ARTICLE optimization algorithms.html 230B
  122. 4. Neural Networks With Backpropagation Theory/12. ARTICLE derivation of backpropagation.html 171B
  123. 2. Neural Networks Introduction/6. ARTICLE activation functions.html 169B
  124. [FreeCourseLab.com].url 126B
  125. 12. Course Materials (DOWNLOADS)/1. Course materials.html 60B