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[] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API

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文件列表

  1. 17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 187MB
  2. 16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.srt 140MB
  3. 16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 140MB
  4. 17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 136MB
  5. 2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 115MB
  6. 17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 111MB
  7. 15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 99MB
  8. 16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 98MB
  9. 2. TensorFlow 2.0 Basics/2. Constants, Variables, Tensors.mp4 71MB
  10. 3. Artificial Neural Networks/2. Data Preprocessing.mp4 62MB
  11. 15. Annex 1 - Artificial Neural Networks Theory/6. Gradient Descent.mp4 61MB
  12. 3. Artificial Neural Networks/3. Building the Artificial Neural Network.mp4 60MB
  13. 3. Artificial Neural Networks/1. Project Setup.mp4 59MB
  14. 11. Fashion API with Flask and TensorFlow 2.0/5. Creating classify function.mp4 53MB
  15. 2. TensorFlow 2.0 Basics/3. Operations with Tensors.mp4 49MB
  16. 3. Artificial Neural Networks/4. Training the Artificial Neural Network.mp4 49MB
  17. 4. Convolutional Neural Networks/1. Project Setup & Data Preprocessing.mp4 47MB
  18. 15. Annex 1 - Artificial Neural Networks Theory/3. The Activation Function.mp4 45MB
  19. 15. Annex 1 - Artificial Neural Networks Theory/8. Backpropagation.mp4 43MB
  20. 2. TensorFlow 2.0 Basics/4. Strings.mp4 40MB
  21. 11. Fashion API with Flask and TensorFlow 2.0/1. Project Setup.mp4 37MB
  22. 3. Artificial Neural Networks/5. Evaluating the Artificial Neural Network.mp4 31MB
  23. 16. Annex 2 - Convolutional Neural Networks Theory/8. Summary.mp4 30MB
  24. 14. Distributed Training with TensorFlow 2.0/3. Dataset preprocessing.mp4 26MB
  25. 12. Image Classification API with TensorFlow Serving/3. Project setup.mp4 26MB
  26. 11. Fashion API with Flask and TensorFlow 2.0/3. Loading a pre-trained model.mp4 20MB
  27. 17. Annex 3 - Recurrent Neural Networks Theory/6. LSTM Variations.mp4 20MB
  28. 16. Annex 2 - Convolutional Neural Networks Theory/1. Plan of Attack.mp4 16MB
  29. 13. TensorFlow Lite Prepare a model for a mobile device/4. Building a model.mp4 15MB
  30. 14. Distributed Training with TensorFlow 2.0/6. Defining a distributed model.mp4 12MB
  31. 15. Annex 1 - Artificial Neural Networks Theory/1. Plan of Attack.mp4 12MB
  32. 17. Annex 3 - Recurrent Neural Networks Theory/1. Plan of Attack.mp4 10MB
  33. 10. Dataset Preprocessing with TensorFlow Transform (TFT)/1. Project Setup.mp4 10MB
  34. 13. TensorFlow Lite Prepare a model for a mobile device/6. Saving the model.mp4 9MB
  35. 14. Distributed Training with TensorFlow 2.0/2. Project Setup.mp4 9MB
  36. 13. TensorFlow Lite Prepare a model for a mobile device/2. Project setup.mp4 8MB
  37. 16. Annex 2 - Convolutional Neural Networks Theory/6. Step 3 - Flattening.mp4 8MB
  38. 11. Fashion API with Flask and TensorFlow 2.0/1.1 Flask API.zip 382KB
  39. 17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.srt 28KB
  40. 15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.srt 25KB
  41. 16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.srt 23KB
  42. 17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.srt 21KB
  43. 17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.srt 21KB
  44. 2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.srt 17KB
  45. 3. Artificial Neural Networks/3. Building the Artificial Neural Network.srt 15KB
  46. 15. Annex 1 - Artificial Neural Networks Theory/6. Gradient Descent.srt 14KB
  47. 2. TensorFlow 2.0 Basics/2. Constants, Variables, Tensors.srt 13KB
  48. 15. Annex 1 - Artificial Neural Networks Theory/3. The Activation Function.srt 12KB
  49. 4. Convolutional Neural Networks/1. Project Setup & Data Preprocessing.srt 11KB
  50. 3. Artificial Neural Networks/2. Data Preprocessing.srt 11KB
  51. 3. Artificial Neural Networks/4. Training the Artificial Neural Network.srt 10KB
  52. 2. TensorFlow 2.0 Basics/4. Strings.srt 9KB
  53. 3. Artificial Neural Networks/1. Project Setup.srt 9KB
  54. 2. TensorFlow 2.0 Basics/3. Operations with Tensors.srt 8KB
  55. 11. Fashion API with Flask and TensorFlow 2.0/1. Project Setup.srt 8KB
  56. 15. Annex 1 - Artificial Neural Networks Theory/8. Backpropagation.srt 7KB
  57. 3. Artificial Neural Networks/5. Evaluating the Artificial Neural Network.srt 7KB
  58. 16. Annex 2 - Convolutional Neural Networks Theory/8. Summary.srt 6KB
  59. 11. Fashion API with Flask and TensorFlow 2.0/5. Creating classify function.srt 6KB
  60. 14. Distributed Training with TensorFlow 2.0/3. Dataset preprocessing.srt 5KB
  61. 16. Annex 2 - Convolutional Neural Networks Theory/1. Plan of Attack.srt 5KB
  62. 12. Image Classification API with TensorFlow Serving/3. Project setup.srt 5KB
  63. 17. Annex 3 - Recurrent Neural Networks Theory/6. LSTM Variations.srt 5KB
  64. 15. Annex 1 - Artificial Neural Networks Theory/1. Plan of Attack.srt 4KB
  65. 11. Fashion API with Flask and TensorFlow 2.0/3. Loading a pre-trained model.srt 4KB
  66. 17. Annex 3 - Recurrent Neural Networks Theory/1. Plan of Attack.srt 4KB
  67. 13. TensorFlow Lite Prepare a model for a mobile device/4. Building a model.srt 3KB
  68. 10. Dataset Preprocessing with TensorFlow Transform (TFT)/1. Project Setup.srt 3KB
  69. 16. Annex 2 - Convolutional Neural Networks Theory/6. Step 3 - Flattening.srt 3KB
  70. 13. TensorFlow Lite Prepare a model for a mobile device/2. Project setup.srt 3KB
  71. 14. Distributed Training with TensorFlow 2.0/6. Defining a distributed model.srt 2KB
  72. 18. Bonus Lectures/3. FREE LEARNING RESOURCES FOR YOU.html 2KB
  73. 13. TensorFlow Lite Prepare a model for a mobile device/10. What's next.html 2KB
  74. 13. TensorFlow Lite Prepare a model for a mobile device/6. Saving the model.srt 2KB
  75. 10. Dataset Preprocessing with TensorFlow Transform (TFT)/6. What's next.html 2KB
  76. 14. Distributed Training with TensorFlow 2.0/2. Project Setup.srt 2KB
  77. 1. Introduction/4. BONUS Learning Path.html 1KB
  78. 18. Bonus Lectures/2. YOUR SPECIAL BONUS.html 1KB
  79. 18. Bonus Lectures/1. SPECIAL COVID-19 BONUS.html 722B
  80. 1. Introduction/3. BONUS 10 advantages of TensorFlow.html 613B
  81. 3. Artificial Neural Networks/7. HOMEWORK Artificial Neural Networks.html 493B
  82. 1. Introduction/2. Course Curriculum & Colab Toolkit.html 464B
  83. 2. TensorFlow 2.0 Basics/1.1 Google Colab TensorFlow 1.x to TensorFlow 2.0.html 134B
  84. 3. Artificial Neural Networks/1.1 Google Colab ANN.html 134B
  85. 4. Convolutional Neural Networks/1.1 Google Colab CNN.html 134B
  86. 1. Introduction/[Tutorialsplanet.NET].url 128B
  87. 18. Bonus Lectures/[Tutorialsplanet.NET].url 128B
  88. 4. Convolutional Neural Networks/[Tutorialsplanet.NET].url 128B
  89. [Tutorialsplanet.NET].url 128B
  90. 3. Artificial Neural Networks/6. Artificial Neural Network Quiz.html 123B