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Packt | Master Deep Learning with TensorFlow 2.0 in Python [2019] [FCO]

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Packt | Master Deep Learning with TensorFlow 2.0 in Python [2019] [FCO]
Packt | Master Deep Learning with TensorFlow 2.0 in Python [2019] [FCO]
Packt | Master Deep Learning with TensorFlow 2.0 in Python [2019] [FCO]
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  1. 0. (1Hack.Us) Premium Tutorials-Guides-Articles & Community based Forum.url 377 bytes
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  6. How you can help Team-FTU.txt 237 bytes
  7. 0101.Meet your instructors and why you should study machine learning.mp4 84.7 MB
  8. 0102.What does the course cover.mp4 39.1 MB
  9. 0201.Introduction to neural networks.mp4 45.7 MB
  10. 0202.Training the model.mp4 26.8 MB
  11. 0203.Types of machine learning.mp4 40.8 MB
  12. 0204.The linear model.mp4 26.0 MB
  13. 0205.The linear model. Multiple inputs.mp4 23.7 MB
  14. 0206.The linear model. Multiple inputs and multiple outputs.mp4 42.2 MB
  15. 0207.Graphical representation.mp4 22.0 MB
  16. 0208.The objective function.mp4 17.7 MB
  17. 0209.L2-norm loss.mp4 21.4 MB
  18. 0210.Cross-entropy loss.mp4 33.4 MB
  19. 0211.One parameter gradient descent.mp4 56.4 MB
  20. 0212.N-parameter gradient descent.mp4 57.6 MB
  21. 0301.Setting up the environment - An introduction - Do not skip, please!.mp4 6.9 MB
  22. 0302.Why Python and why Jupyter.mp4 34.7 MB
  23. 0303.Installing Anaconda.mp4 31.3 MB
  24. 0304.The Jupyter dashboard - part 1.mp4 9.2 MB
  25. 0305.The Jupyter dashboard - part 2.mp4 20.4 MB
  26. 0306.Installing TensorFlow 2.mp4 51.2 MB
  27. 0401.Minimal example - part 1.mp4 36.4 MB
  28. 0402.Minimal example - part 2.mp4 23.7 MB
  29. 0403.Minimal example - part 3.mp4 20.4 MB
  30. 0404.Minimal example - part 4.mp4 30.4 MB
  31. 0501.TensorFlow outline.mp4 42.0 MB
  32. 0502.TensorFlow 2 intro.mp4 37.8 MB
  33. 0503.A Note on Coding in TensorFlow.mp4 8.1 MB
  34. 0504.Types of file formats in TensorFlow and data handling.mp4 13.3 MB
  35. 0505.Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.mp4 32.9 MB
  36. 0506.Interpreting the result and extracting the weights and bias.mp4 31.4 MB
  37. 0507.Customizing your model.mp4 21.6 MB
  38. 0601.Layers.mp4 20.5 MB
  39. 0602.What is a deep net.mp4 32.6 MB
  40. 0603.Understanding deep nets in depth.mp4 58.2 MB
  41. 0604.Why do we need non-linearities.mp4 38.0 MB
  42. 0605.Activation functions.mp4 38.0 MB
  43. 0606.Softmax activation.mp4 25.0 MB
  44. 0607.Backpropagation.mp4 52.7 MB
  45. 0608.Backpropagation - visual representation.mp4 24.4 MB
  46. 0701.Underfitting and overfitting.mp4 34.1 MB
  47. 0702.Underfitting and overfitting - classification.mp4 32.5 MB
  48. 0703.Training and validation.mp4 37.5 MB
  49. 0704.Training, validation, and test.mp4 31.3 MB
  50. 0705.N-fold cross validation.mp4 25.6 MB
  51. 0706.Early stopping.mp4 28.3 MB
  52. 0801.Initialization - Introduction.mp4 26.2 MB
  53. 0802.Types of simple initializations.mp4 12.3 MB
  54. 0803.Xavier initialization.mp4 19.1 MB
  55. 0901.Stochastic gradient descent.mp4 34.5 MB
  56. 0902.Gradient descent pitfalls.mp4 14.3 MB
  57. 0903.Momentum.mp4 19.0 MB
  58. 0904.Learning rate schedules.mp4 37.1 MB
  59. 0905.Learning rate schedules. A picture.mp4 10.9 MB
  60. 0906.Adaptive learning rate schedules.mp4 29.8 MB
  61. 0907.Adaptive moment estimation.mp4 29.1 MB
  62. 1001.Preprocessing introduction.mp4 25.6 MB
  63. 1002.Basic preprocessing.mp4 11.1 MB
  64. 1003.Standardization.mp4 40.4 MB
  65. 1004.Dealing with categorical data.mp4 18.2 MB
  66. 1005.One-hot and binary encoding.mp4 32.3 MB
  67. 1101.The dataset.mp4 20.7 MB
  68. 1102.How to tackle the MNIST.mp4 33.3 MB
  69. 1103.Importing the relevant packages and load the data.mp4 15.8 MB
  70. 1104.Preprocess the data - create a validation dataset and scale the data.mp4 27.1 MB
  71. 1105.Preprocess the data - shuffle and batch the data.mp4 36.6 MB
  72. 1106.Outline the model.mp4 27.4 MB
  73. 1107.Select the loss and the optimizer.mp4 12.7 MB
  74. 1108.Learning.mp4 20.4 MB
  75. 1109.Testing the model.mp4 15.3 MB
  76. 1201.Exploring the dataset and identifying predictors.mp4 30.2 MB
  77. 1202.Outlining the business case solution.mp4 9.5 MB
  78. 1203.Balancing the dataset.mp4 13.7 MB
  79. 1204.Preprocessing the data.mp4 44.5 MB
  80. 1205.Load the preprocessed data.mp4 18.2 MB
  81. 1206.Learning and interpreting the result.mp4 26.4 MB
  82. 1207.Setting an early stopping mechanism.mp4 21.5 MB
  83. 1208.Testing the model.mp4 9.6 MB
  84. 1301.See how much you have learned.mp4 38.9 MB
  85. 1302.What's further out there in the machine and deep learning world.mp4 17.5 MB
  86. 1303.An overview of CNNs.mp4 18.6 MB
  87. 1304.An overview of RNNs.mp4 27.4 MB
  88. 1305.An overview of non-NN approaches.mp4 40.2 MB
  89. exercise_files.zip 1.4 MB

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