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   源码介绍

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[machine_learning_mastery系列]deep_learning_with_python.pdf(with code)
I created this book because I thought that there was no gentle way for Python machine learning practitioners to quickly get started developing deep learning models. In developing the lessons in this ...

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├── [machine_learning_mastery系列]deep_learning_with_python.pdf(with code)_deep_learning_with_python.zip
└── deep_learning_with_python
    ├── deep_learning_with_python_code
    │   ├── callbacks
    │   │   ├── callbacks_checkpoint_best.py
    │   │   ├── callbacks_checkpoint_improvements.py
    │   │   ├── callbacks_checkpoint_load.py
    │   │   ├── callbacks_early_stopping.py
    │   │   ├── callbacks_history_visualize.py
    │   │   └── callbacks_history_visualize_save.py
    │   ├── data
    │   │   ├── builtin-datasets.py
    │   │   ├── housing.csv
    │   │   ├── ionosphere.csv
    │   │   ├── iris.csv
    │   │   ├── pima-indians-diabetes.csv
    │   │   └── sonar.csv
    │   ├── data_augmentation
    │   │   ├── random_flips.py
    │   │   ├── random_rotations.py
    │   │   ├── random_shear.py
    │   │   ├── random_shifts.py
    │   │   ├── save_augmented_images.py
    │   │   ├── standardize_features.py
    │   │   ├── standardize_samples.py
    │   │   └── zca_whitening.py
    │   ├── data_preparation
    │   │   ├── label_encode.py
    │   │   ├── normalization.py
    │   │   ├── one_hot_encoding.py
    │   │   └── standardize.py
    │   ├── evaluation
    │   │   ├── mlp_auto_validation.py
    │   │   ├── mlp_manual_cv.py
    │   │   └── mlp_manual_validation.py
    │   ├── learning_rate
    │   │   ├── baseline.py
    │   │   ├── step_decay.py
    │   │   └── time_decay.py
    │   ├── project-cifar10
    │   │   ├── cnn_augment.py
    │   │   ├── cnn_large.py
    │   │   ├── cnn_simple.py
    │   │   └── plot-cifar10.py
    │   ├── project-imdb
    │   │   ├── imdb_cnn.py
    │   │   ├── imdb_cnn_big_maxpool.py
    │   │   ├── imdb_cnn_big_maxpool_dropout.py
    │   │   ├── imdb_mlp.py
    │   │   ├── imdb_mlp_dropout.py
    │   │   └── imdb_summarize.py
    │   ├── project-mlp
    │   │   ├── binary_classification_diabetes.py
    │   │   ├── binary_classification_ionosphere.py
    │   │   ├── binary_classification_sonar.py
    │   │   ├── mlp_first.py
    │   │   ├── multiclass_classification_iris.py
    │   │   └── regression_boston.py
    │   ├── project-mnist
    │   │   ├── cnn_augmentation.py
    │   │   ├── cnn_mnist_deep.py
    │   │   ├── cnn_mnist_simple.py
    │   │   ├── mlp_mnist.py
    │   │   └── plot_mnist.py
    │   ├── regularization
    │   │   ├── activation_regularization.py
    │   │   ├── batch_normalization.py
    │   │   ├── dropout.py
    │   │   ├── weight_constraint.py
    │   │   └── weight_regularization.py
    │   ├── scikit-learn
    │   │   ├── grid_search_learning_rate.py
    │   │   ├── grid_search_training.py
    │   │   └── mlp_sklearn_cv.py
    │   └── serialize
    │       ├── mlp_json.py
    │       └── mlp_yaml.py
    └── deep_learning_with_python_code.zip

15 directories, 63 files