##5. Create object(model)
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
model = Sequential()
model.add(Dense(100, input_shape = (784, ), activation = 'relu')) #1st floor
model.add(Dense(50, activation = 'relu')) #2nd
model.add(Dense(10, activation='softmax') ) #3rd
##6. Compile object (object=model)
from tensorflow.keras.losses import categorical_crossentropy
model.compile(optimizer = 'SGD',
loss = 'categorical_crossentropy',
metrics = ['acc'] )
# learning rate default : 0.001
##7. Fitting object (object=model)
history = model.fit( x_train, y_train, epochs=30, batch_size=100, validation_data=(x_val, y_val) )
##8. Verify trained object
results = model.predict(x_test)
print(results)
##9. Results
import numpy as np
pred = np.argmax(results, axis=1)
label = np.argmax(y_test, axis=1)
a = pred==label
a.astype(int).sum() / len(a) #0.9564 # 정확도