[FreeCoursesOnline.Me] [Packt] Troubleshooting Python Deep Learning [FCO]

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[FreeCoursesOnline.Me] [Packt] Troubleshooting Python Deep Learning [FCO]

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种子哈希：7a926261c20a3a094bf62859a65c8f5f4718819a
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收录时间：2021-03-22
最近下载：2024-12-31

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文件列表

  • 1. Solutions to Convolutional Neural Network Problems – Part One_/02.Concatenate Two CNNs Correctly.mp4 77.6 MB
  • 1. Solutions to Convolutional Neural Network Problems – Part One_/01.The Course Overview.mp4 39.5 MB
  • 6. Solving NumPy Problems_/44.Turn ND Matrix Into 1D Vector.mp4 31.5 MB
  • 6. Solving NumPy Problems_/43.Fix load.npy Error in Python3.mp4 17.3 MB
  • 4.Solutions to LSTM Recurrent Neural Networks Problems/27.Working with Different Lengths of Input and Output Sequences.mp4 16.4 MB
  • 1. Solutions to Convolutional Neural Network Problems – Part One_/03.Splitting Trained Model.mp4 13.8 MB
  • 3. Solutions to Recurrent Neural Network Problems_/19.Wrong Input - ValueError – Error When Checking Input.mp4 13.8 MB
  • 5. Troubleshooting Models with scikit-learn_/35.Handling Missing Values.mp4 13.3 MB
  • 4.Solutions to LSTM Recurrent Neural Networks Problems/32.How To Do Text Classification with LSTM.mp4 11.9 MB
  • 1. Solutions to Convolutional Neural Network Problems – Part One_/06.High val_acc, But Low Accuracy in Practice.mp4 11.6 MB
  • 3. Solutions to Recurrent Neural Network Problems_/20.Correct Text Preparation for Machine Translation.mp4 11.0 MB
  • 5. Troubleshooting Models with scikit-learn_/37.Fixing Warning Messages.mp4 10.8 MB
  • 2. Solutions to Convolutional Neural Network Problems – Part Two_/11.Interpreting kernel_size Notation in CNNs.mp4 10.4 MB
  • 3. Solutions to Recurrent Neural Network Problems_/24.Preparing Data Correctly for Time Series Prediction.mp4 10.1 MB
  • 4.Solutions to LSTM Recurrent Neural Networks Problems/26.Stacking Multiple LSTM in Keras TypeError - Call() Got an Unexpected Keyword Argument 'return_sequences'.mp4 10.1 MB
  • 2. Solutions to Convolutional Neural Network Problems – Part Two_/13.Using Validation Accuracy.mp4 9.3 MB
  • 5. Troubleshooting Models with scikit-learn_/36.Evaluating Deep Learning Models Using Additional Metrics.mp4 9.1 MB
  • 2. Solutions to Convolutional Neural Network Problems – Part Two_/17.Shape Error When Training CIFAR-10 Dataset on CNN.mp4 9.1 MB
  • 6. Solving NumPy Problems_/41.Converting a 2D Matrix to a One-Hot Encoded Matrix.mp4 9.0 MB
  • 4.Solutions to LSTM Recurrent Neural Networks Problems/29.Using CNN-LSTM for Time Series Prediction.mp4 8.9 MB
  • 2. Solutions to Convolutional Neural Network Problems – Part Two_/14.Error When Using CNN to Classify Text.mp4 8.7 MB
  • 5. Troubleshooting Models with scikit-learn_/40.Preparing Text for Use with Deep Learning Models.mp4 8.6 MB
  • 3. Solutions to Recurrent Neural Network Problems_/18.Building an RNN Model in Keras.mp4 8.5 MB
  • 1. Solutions to Convolutional Neural Network Problems – Part One_/09.Model That Uses Dropout Is Still Overfitting.mp4 8.5 MB
  • 5. Troubleshooting Models with scikit-learn_/34.LabelBinarizer Returns Vector When There Are Two Classes.mp4 8.3 MB
  • 3. Solutions to Recurrent Neural Network Problems_/21.Handling Invalid Input Shape Error.mp4 8.3 MB
  • 4.Solutions to LSTM Recurrent Neural Networks Problems/33.Data Preparation for Seq2Seq Learning.mp4 8.1 MB
  • 1. Solutions to Convolutional Neural Network Problems – Part One_/04.Resolving fit_generator Errors.mp4 8.0 MB
  • 2. Solutions to Convolutional Neural Network Problems – Part Two_/16.Common Problems When Using Pre-Trained CNN Models.mp4 8.0 MB
  • 2. Solutions to Convolutional Neural Network Problems – Part Two_/12.Choosing Last Layer’s Activation Function in CNN.mp4 7.9 MB
  • 3. Solutions to Recurrent Neural Network Problems_/22.Mapping Series of Vectors to a Single Vector.mp4 7.4 MB
  • 3. Solutions to Recurrent Neural Network Problems_/25.How to Enable Stateful RNN.mp4 7.3 MB
  • 5. Troubleshooting Models with scikit-learn_/38.Generating Test Datasets.mp4 7.2 MB
  • 5. Troubleshooting Models with scikit-learn_/39.Normalizing and Standardizing the Data.mp4 7.2 MB
  • 2. Solutions to Convolutional Neural Network Problems – Part Two_/10.When the Value Error Input 0 Is Incompatible with Layer conv2d_1.mp4 6.7 MB
  • 3. Solutions to Recurrent Neural Network Problems_/23.Resolving a Bad Output from RNN While Generating a Simple Sequence.mp4 6.6 MB
  • 4.Solutions to LSTM Recurrent Neural Networks Problems/28.How to Use Stacked LSTMs.mp4 6.4 MB
  • 4.Solutions to LSTM Recurrent Neural Networks Problems/30.Solving LSTM Underfitting on Time Series Problem.mp4 6.3 MB
  • 2. Solutions to Convolutional Neural Network Problems – Part Two_/15.Kernel Weight Initialization in CNN Model.mp4 5.6 MB
  • 4.Solutions to LSTM Recurrent Neural Networks Problems/31.Using LSTM for Multi-Value Prediction.mp4 5.5 MB
  • 6. Solving NumPy Problems_/42.Reshaping a 2D NumPy Array to 3D Array.mp4 5.1 MB
  • 1. Solutions to Convolutional Neural Network Problems – Part One_/07.Error in Adding a Dense Layer.mp4 5.1 MB
  • 1. Solutions to Convolutional Neural Network Problems – Part One_/08.Model with Multiple Outputs Errors.mp4 4.0 MB
  • 1. Solutions to Convolutional Neural Network Problems – Part One_/05.Model Object Has No Attribute load_model Keras.mp4 3.3 MB
  • Exercise Files/code_37489.zip 2.0 kB
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