Keras 深度学习入门
Miguel Esteban
Data Scientist & Founder
# 拟合已构建并编译的模型 model.fit(X_train, y_train, epochs=100, batch_size=128) ^^^^^^^^^^^^^^
# 从 keras layers 导入 BatchNormalization from tensorflow.keras.layers import BatchNormalization # 实例化 Sequential 模型 model = Sequential() # 添加输入层 model.add(Dense(3, input_shape=(2,), activation = 'relu')) # 为上一层的输出添加批归一化 model.add(BatchNormalization()) # 添加输出层 model.add(Dense(1, activation='sigmoid'))
# 从 keras layers 导入 BatchNormalization from tensorflow.keras.layers import BatchNormalization
# 实例化 Sequential 模型 model = Sequential()
# 添加输入层 model.add(Dense(3, input_shape=(2,), activation = 'relu'))
# 为上一层的输出添加批归一化 model.add(BatchNormalization())
# 添加输出层 model.add(Dense(1, activation='sigmoid'))
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