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种子名称： [FreeCoursesOnline.Me] [Packt] Troubleshooting Python Deep Learning [FCO]
文件类型： 视频
文件数目： 44个文件
文件大小： 487.39 MB
收录时间： 2019-8-18 15:44
已经下载： 3次
资源热度： 102
最近下载： 2024-9-29 02:01

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

1. Solutions to Convolutional Neural Network Problems – Part One_/01.The Course Overview.mp437.64MB

1. Solutions to Convolutional Neural Network Problems – Part One_/02.Concatenate Two CNNs Correctly.mp473.99MB

1. Solutions to Convolutional Neural Network Problems – Part One_/03.Splitting Trained Model.mp413.19MB

1. Solutions to Convolutional Neural Network Problems – Part One_/04.Resolving fit_generator Errors.mp47.63MB

1. Solutions to Convolutional Neural Network Problems – Part One_/05.Model Object Has No Attribute load_model Keras.mp43.19MB

1. Solutions to Convolutional Neural Network Problems – Part One_/06.High val_acc, But Low Accuracy in Practice.mp411.03MB

1. Solutions to Convolutional Neural Network Problems – Part One_/07.Error in Adding a Dense Layer.mp44.83MB

1. Solutions to Convolutional Neural Network Problems – Part One_/08.Model with Multiple Outputs Errors.mp43.86MB

1. Solutions to Convolutional Neural Network Problems – Part One_/09.Model That Uses Dropout Is Still Overfitting.mp48.09MB

2. Solutions to Convolutional Neural Network Problems – Part Two_/10.When the Value Error Input 0 Is Incompatible with Layer conv2d_1.mp46.42MB

2. Solutions to Convolutional Neural Network Problems – Part Two_/11.Interpreting kernel_size Notation in CNNs.mp49.92MB

2. Solutions to Convolutional Neural Network Problems – Part Two_/12.Choosing Last Layer’s Activation Function in CNN.mp47.53MB

2. Solutions to Convolutional Neural Network Problems – Part Two_/13.Using Validation Accuracy.mp48.82MB

2. Solutions to Convolutional Neural Network Problems – Part Two_/14.Error When Using CNN to Classify Text.mp48.3MB

2. Solutions to Convolutional Neural Network Problems – Part Two_/15.Kernel Weight Initialization in CNN Model.mp45.36MB

2. Solutions to Convolutional Neural Network Problems – Part Two_/16.Common Problems When Using Pre-Trained CNN Models.mp47.6MB

2. Solutions to Convolutional Neural Network Problems – Part Two_/17.Shape Error When Training CIFAR-10 Dataset on CNN.mp48.68MB

3. Solutions to Recurrent Neural Network Problems_/18.Building an RNN Model in Keras.mp48.12MB

3. Solutions to Recurrent Neural Network Problems_/19.Wrong Input - ValueError – Error When Checking Input.mp413.17MB

3. Solutions to Recurrent Neural Network Problems_/20.Correct Text Preparation for Machine Translation.mp410.45MB

3. Solutions to Recurrent Neural Network Problems_/21.Handling Invalid Input Shape Error.mp47.89MB

3. Solutions to Recurrent Neural Network Problems_/22.Mapping Series of Vectors to a Single Vector.mp47.01MB

3. Solutions to Recurrent Neural Network Problems_/23.Resolving a Bad Output from RNN While Generating a Simple Sequence.mp46.26MB

3. Solutions to Recurrent Neural Network Problems_/24.Preparing Data Correctly for Time Series Prediction.mp49.66MB

3. Solutions to Recurrent Neural Network Problems_/25.How to Enable Stateful RNN.mp46.99MB

4.Solutions to LSTM Recurrent Neural Networks Problems/26.Stacking Multiple LSTM in Keras TypeError - Call() Got an Unexpected Keyword Argument 'return_sequences'.mp49.61MB

4.Solutions to LSTM Recurrent Neural Networks Problems/27.Working with Different Lengths of Input and Output Sequences.mp415.61MB

4.Solutions to LSTM Recurrent Neural Networks Problems/28.How to Use Stacked LSTMs.mp46.13MB

4.Solutions to LSTM Recurrent Neural Networks Problems/29.Using CNN-LSTM for Time Series Prediction.mp48.48MB

4.Solutions to LSTM Recurrent Neural Networks Problems/30.Solving LSTM Underfitting on Time Series Problem.mp46.03MB

4.Solutions to LSTM Recurrent Neural Networks Problems/31.Using LSTM for Multi-Value Prediction.mp45.29MB

4.Solutions to LSTM Recurrent Neural Networks Problems/32.How To Do Text Classification with LSTM.mp411.39MB

4.Solutions to LSTM Recurrent Neural Networks Problems/33.Data Preparation for Seq2Seq Learning.mp47.7MB

5. Troubleshooting Models with scikit-learn_/34.LabelBinarizer Returns Vector When There Are Two Classes.mp47.95MB

5. Troubleshooting Models with scikit-learn_/35.Handling Missing Values.mp412.64MB

5. Troubleshooting Models with scikit-learn_/36.Evaluating Deep Learning Models Using Additional Metrics.mp48.7MB

5. Troubleshooting Models with scikit-learn_/37.Fixing Warning Messages.mp410.3MB

5. Troubleshooting Models with scikit-learn_/38.Generating Test Datasets.mp46.9MB

5. Troubleshooting Models with scikit-learn_/39.Normalizing and Standardizing the Data.mp46.84MB

5. Troubleshooting Models with scikit-learn_/40.Preparing Text for Use with Deep Learning Models.mp48.18MB

6. Solving NumPy Problems_/41.Converting a 2D Matrix to a One-Hot Encoded Matrix.mp48.55MB

6. Solving NumPy Problems_/42.Reshaping a 2D NumPy Array to 3D Array.mp44.84MB

6. Solving NumPy Problems_/43.Fix load.npy Error in Python3.mp416.54MB

6. Solving NumPy Problems_/44.Turn ND Matrix Into 1D Vector.mp430.07MB