text_plain_output_1.png
from keras.layers import Dense, Dropout

from keras.models import Sequential

X_train_matrix = X_train_matrix.astype('float32') / 255
X_test_matrix = X_test_matrix.astype('float32') / 255

from keras.models import Sequential
from keras.layers import Dense, Dropout
model = Sequential()
model.add(Dense(784, input_shape=(len(X_train_matrix[0]),)))
model.add(Dense(392, activation='relu'))
model.add(Dropout(0.2))
model.add(Dense(196, activation='relu'))
model.add(Dropout(0.2))
model.add(Dense(10, activation='softmax'))
model.summary()