Day25 参加职训(机器学习与资料分析工程师培训班)，Python程式设计

建立网路的其他写法

from tensorflow.keras.models import Sequentialfrom tensorflow.keras.layers import DenseModel01 = Sequential([Dense(512, activation='relu', input_dim=3),                      Dense(1, activation='sigmoid')])

from tensorflow.keras.models import Sequentialfrom tensorflow.keras.layers import Densefrom tensorflow.keras.layers import ActivationModel02 = Sequential([Dense(512, input_dim=3), Activation('relu'),                     Dense(1), Activation('sigmoid')])Model02.summary()

# 储存网路配置 configConfig_Model02 = Model02.get_config()from tensorflow.keras.models import SequentialModel03 = Sequential.from_config(Config_Model02)Model03.summary()  #会发现与Model02的网路一样# 储存网路配置 jsonConfig_json_Model03 = Model03.to_json()from tensorflow.keras.models import model_from_jsonModel04 = model_from_json(Config_json_Model03)

# 取得权重model_weights = model.get_weights()# 储存权重MNIST_Model.save_weights('MNIST.Weights')# 回复权重model06.load_weights('MNIST.Weights')

from tensorflow.keras.optimizers import RMSprop# 修改优化器的预设值My_RMSprop = RMSprop(learning_rate=0.01)MNIST_Model.compile(optimizer=My_RMSprop, loss = 'categorical_crossentropy', metrics=['accuracy'])MNIST_Model.fit(X_train, y_train, epochs=5, batch_size=128, verbose=1)