Deep-Learning-Course/ThirdSaturday/keras_mnist.py

18 lines
744 B
Python

from keras.layers import Dense, Activation
from keras.optimizers import RMSprop
from keras.models import Sequential
from keras import losses
from keras.models import Sequential
model = Sequential([Dense(units=64, input_dim=784),
Activation('relu'),
Dense(units=10),
Activation('softmax')])
model = Sequential([Dense(units=64, input_dim=784),
Activation('relu'),
Dense(units=10),
Activation('softmax')])
model.compile(optimizer=RMSprop(lr=0.001, rho=0.9, epsilon=1e-08, decay=0.0), loss=losses.,metrics=['accuracy'])
model.fit(xtrain.images,xtrain.labels,batch_size=10,epochs=10,validation_data=(xtest.images,xtest.labes))