text_plain_output_2.png text_plain_output_1.png
from keras.layers import Dense, Input, Dropout

from keras.models import Sequential

model = Sequential()
model.add(Dense(X_train.shape[1], input_shape=(784,), activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(y_train.shape[1], activation='softmax'))

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

model.fit(X_train, y_train, validation_data=(X_test, y_test), epochs=5, batch_size=100)