import tensorflow as tf
from tensorflow import keras

minst=tf.keras.datasets.mnist

(x_train, y_train),(x_test, y_test) = minst.load_data()
x_train=x_train/255.0
x_test=x_test/255.0
model=tf.keras.models.Sequential([
    tf.keras.layers.Flatten(input_shape=(28,28)),
    tf.keras.layers.Dense(units=512,activation=tf.nn.relu),
    tf.keras.layers.Dense(units=10,activation=tf.nn.softmax)
])

model.compile(optimizer='adam',loss='sparse_categorical_crossentropy')

model.fit(x_test,y_test,epochs=10)
