Keras-Outline

Blog

https://blog.keras.io/
https://github.com/fchollet/keras-blog

Demo

Keras as a simplified interface to TensorFlow: tutorial https://blog.keras.io/keras-as-a-simplified-interface-to-tensorflow-tutorial.html

Document

https://keras.io/getting-started/sequential-model-guide/

• Models
  
  • Sequential
  • Model(Functional API)
• Layers
  
  • core Layers
  • Convolutional Layers
    
    • https://keras-cn.readthedocs.io/en/latest/layers/convolutional_layer/
  • Pooling Layers
  • Locally-connected Layers
  • Recurrent Layers
  • Embedding Layers
  • Merge Layers
  • Advanced Activations Layers
  • Normalization Layers
  • Noise Layers
  • Layer Wappers
  • Writing your own Keras Layers
• Preprocessing
  
  • Sequence
  • Text
  • Image
• Losses
• Metrics
• Optimizers
• Activations
• Callbacks
• Datasets
• Applications
• Backend
• Initializers
  
  • Initialize method
    
    • https://keras-cn.readthedocs.io/en/latest/other/initializations/
• Regularizers
• Constraints
• Visualization
• SKLearn API
• Utils
  
  • to_categorical
    
# 将类别向量(从0到nb_classes的整数向量)映射为二值类别矩阵，
# 相当于将向量用one-hot重新编码
Y_train = np_utils.to_categorical(y_train, nb_classes)
# y_train 5, 0, 4,....
#Y_train [ 0. 0. 0. 0. 0. 1. 0. 0. 0. 0.], [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 0.],[ 0. 0. 0. 0. 1. 0. 0. 0. 0. 0.]
Y_test = np_utils.to_categorical(y_test, nb_classes)