Handwritten Number Predictor (Machine Learning)

import tensorflow as tf
import keras
import numpy as np

mnist = keras.datasets.mnist

(x_train, y_train),(x_test, y_test) = mnist.load_data()

x_train = keras.utils.normalize(x_train, axis=1)

x_test = keras.utils.normalize(x_test, axis=1)

model = keras.models.Sequential()

model.add(keras.layers.Flatten(input_shape=(28,28)))
model.add(keras.layers.Dense(128, activation=tf.nn.relu))
model.add(keras.layers.Dense(128, activation=tf.nn.relu))
model.add(keras.layers.Dense(10, activation=tf.nn.softmax))

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

model.fit(x_train,y_train,epochs=1)

val_loss , val_acc = model.evaluate(x_test, y_test)
print(val_loss, val_acc)

prediction = model.predict([x_test])
print(np.argmax(prediction[0]))

OUTPUT:

7