MLP (multilayer perceptron neural network) is a multilayer fully connected neural network model.

MLP（ Multilayer perceptron neural network ） That is, multi-layer fully connected neural network model .

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        from keras.datasets import mnist
        
from keras.utils import np_utils
        
from keras.models import Sequential
        
from keras.layers import Dense,Dropout,Activation
        

        
batch_size=128
        
nb_classes=10
        
nb_epoch=10
        
img_size=28*28
        

        
(x_train,y_train),(x_test,y_test)=mnist.load_data("E:\Code\PycharmProjects\KerasStudying\data\mnist.npz")
        

        
x_train=x_train.reshape(-1,img_size).astype('float32')/255
        
x_test=x_test.reshape(-1,img_size).astype('float32')/255
        
y_train=np_utils.to_categorical(y_train,nb_classes)
        
y_test=np_utils.to_categorical(y_test,nb_classes)
        

        

        
model=Sequential([
        
    Dense(512,input_shape=(img_size,),activation='relu',),
        
    Dropout(0.2),
        
    Dense(512,input_shape=(512,),activation='relu'),
        
    Dropout(0.2),
        
    Dense(10,input_shape=(512,),activation='softmax'),
        
])
        

        
model.summary()
        

        
model.compile(optimizer='rmsprop',loss='categorical_crossentropy',metrics=['accuracy'])
        

        

        
model.fit(x_train,y_train,batch_size=batch_size,epochs=10,verbose=0,validation_data=(x_test,y_test))
        

        
score=model.evaluate(x_test,y_test,verbose=0)
        
print('accuracy:'+str(score[1]))
       
       

        
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