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[] [Packt] Troubleshooting Python Deep Learning [FCO]

  • 收录时间:2020-02-21 16:54:17
  • 文件大小:487MB
  • 下载次数:52
  • 最近下载:2020-12-22 16:35:50
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文件列表

  1. 1. Solutions to Convolutional Neural Network Problems – Part One_/02.Concatenate Two CNNs Correctly.mp4 74MB
  2. 1. Solutions to Convolutional Neural Network Problems – Part One_/01.The Course Overview.mp4 38MB
  3. 6. Solving NumPy Problems_/44.Turn ND Matrix Into 1D Vector.mp4 30MB
  4. 6. Solving NumPy Problems_/43.Fix load.npy Error in Python3.mp4 17MB
  5. 4.Solutions to LSTM Recurrent Neural Networks Problems/27.Working with Different Lengths of Input and Output Sequences.mp4 16MB
  6. 1. Solutions to Convolutional Neural Network Problems – Part One_/03.Splitting Trained Model.mp4 13MB
  7. 3. Solutions to Recurrent Neural Network Problems_/19.Wrong Input - ValueError – Error When Checking Input.mp4 13MB
  8. 5. Troubleshooting Models with scikit-learn_/35.Handling Missing Values.mp4 13MB
  9. 4.Solutions to LSTM Recurrent Neural Networks Problems/32.How To Do Text Classification with LSTM.mp4 11MB
  10. 1. Solutions to Convolutional Neural Network Problems – Part One_/06.High val_acc, But Low Accuracy in Practice.mp4 11MB
  11. 3. Solutions to Recurrent Neural Network Problems_/20.Correct Text Preparation for Machine Translation.mp4 10MB
  12. 5. Troubleshooting Models with scikit-learn_/37.Fixing Warning Messages.mp4 10MB
  13. 2. Solutions to Convolutional Neural Network Problems – Part Two_/11.Interpreting kernel_size Notation in CNNs.mp4 10MB
  14. 3. Solutions to Recurrent Neural Network Problems_/24.Preparing Data Correctly for Time Series Prediction.mp4 10MB
  15. 4.Solutions to LSTM Recurrent Neural Networks Problems/26.Stacking Multiple LSTM in Keras TypeError - Call() Got an Unexpected Keyword Argument 'return_sequences'.mp4 10MB
  16. 2. Solutions to Convolutional Neural Network Problems – Part Two_/13.Using Validation Accuracy.mp4 9MB
  17. 5. Troubleshooting Models with scikit-learn_/36.Evaluating Deep Learning Models Using Additional Metrics.mp4 9MB
  18. 2. Solutions to Convolutional Neural Network Problems – Part Two_/17.Shape Error When Training CIFAR-10 Dataset on CNN.mp4 9MB
  19. 6. Solving NumPy Problems_/41.Converting a 2D Matrix to a One-Hot Encoded Matrix.mp4 9MB
  20. 4.Solutions to LSTM Recurrent Neural Networks Problems/29.Using CNN-LSTM for Time Series Prediction.mp4 8MB
  21. 2. Solutions to Convolutional Neural Network Problems – Part Two_/14.Error When Using CNN to Classify Text.mp4 8MB
  22. 5. Troubleshooting Models with scikit-learn_/40.Preparing Text for Use with Deep Learning Models.mp4 8MB
  23. 3. Solutions to Recurrent Neural Network Problems_/18.Building an RNN Model in Keras.mp4 8MB
  24. 1. Solutions to Convolutional Neural Network Problems – Part One_/09.Model That Uses Dropout Is Still Overfitting.mp4 8MB
  25. 5. Troubleshooting Models with scikit-learn_/34.LabelBinarizer Returns Vector When There Are Two Classes.mp4 8MB
  26. 3. Solutions to Recurrent Neural Network Problems_/21.Handling Invalid Input Shape Error.mp4 8MB
  27. 4.Solutions to LSTM Recurrent Neural Networks Problems/33.Data Preparation for Seq2Seq Learning.mp4 8MB
  28. 1. Solutions to Convolutional Neural Network Problems – Part One_/04.Resolving fit_generator Errors.mp4 8MB
  29. 2. Solutions to Convolutional Neural Network Problems – Part Two_/16.Common Problems When Using Pre-Trained CNN Models.mp4 8MB
  30. 2. Solutions to Convolutional Neural Network Problems – Part Two_/12.Choosing Last Layer’s Activation Function in CNN.mp4 8MB
  31. 3. Solutions to Recurrent Neural Network Problems_/22.Mapping Series of Vectors to a Single Vector.mp4 7MB
  32. 3. Solutions to Recurrent Neural Network Problems_/25.How to Enable Stateful RNN.mp4 7MB
  33. 5. Troubleshooting Models with scikit-learn_/38.Generating Test Datasets.mp4 7MB
  34. 5. Troubleshooting Models with scikit-learn_/39.Normalizing and Standardizing the Data.mp4 7MB
  35. 2. Solutions to Convolutional Neural Network Problems – Part Two_/10.When the Value Error Input 0 Is Incompatible with Layer conv2d_1.mp4 6MB
  36. 3. Solutions to Recurrent Neural Network Problems_/23.Resolving a Bad Output from RNN While Generating a Simple Sequence.mp4 6MB
  37. 4.Solutions to LSTM Recurrent Neural Networks Problems/28.How to Use Stacked LSTMs.mp4 6MB
  38. 4.Solutions to LSTM Recurrent Neural Networks Problems/30.Solving LSTM Underfitting on Time Series Problem.mp4 6MB
  39. 2. Solutions to Convolutional Neural Network Problems – Part Two_/15.Kernel Weight Initialization in CNN Model.mp4 5MB
  40. 4.Solutions to LSTM Recurrent Neural Networks Problems/31.Using LSTM for Multi-Value Prediction.mp4 5MB
  41. 6. Solving NumPy Problems_/42.Reshaping a 2D NumPy Array to 3D Array.mp4 5MB
  42. 1. Solutions to Convolutional Neural Network Problems – Part One_/07.Error in Adding a Dense Layer.mp4 5MB
  43. 1. Solutions to Convolutional Neural Network Problems – Part One_/08.Model with Multiple Outputs Errors.mp4 4MB
  44. 1. Solutions to Convolutional Neural Network Problems – Part One_/05.Model Object Has No Attribute load_model Keras.mp4 3MB
  45. Exercise Files/code_37489.zip 2KB
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