modelo = keras.Sequential([ keras.layers.Flatten(input_shape = (28,28)), keras.layers.Dense(256, activation = tensorflow.nn.relu), keras.layers.Dense(10, activation = tensorflow.nn.softmax)])
modelo.compile(optimizer='adam', loss='sparse_categorical_crossentropy')
modelo.fit(imagens_treino, identificacoes_treino)
1875/1875 [==============================] - 4s 2ms/step - loss: 3.9493 <tensorflow.python.keras.callbacks.History at 0x7f6bcad69080>
#so esta carregando 1875 imagens e as variáveis de teste só 313 iagens
