Update app.py

app.py

@@ -1,31 +1,3 @@
 import tensorflow as tf
 print("TensorFlow version:", tf.__version__)
 
-mnist = tf.keras.datasets.mnist
-
-(x_train, y_train), (x_test, y_test) = mnist.load_data()
-x_train, x_test = x_train / 255.0, x_test / 255.0
-
-model = tf.keras.models.Sequential([
-  tf.keras.layers.Flatten(input_shape=(28, 28)),
-  tf.keras.layers.Dense(128, activation='relu'),
-  tf.keras.layers.Dropout(0.2),
-  tf.keras.layers.Dense(10)
-])
-
-predictions = model(x_train[:1]).numpy()
-predictions
-
-tf.nn.softmax(predictions).numpy()
-
-loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)
-
-loss_fn(y_train[:1], predictions).numpy()
-
-model.compile(optimizer='adam',
-              loss=loss_fn,
-              metrics=['accuracy'])
-
-model.fit(x_train, y_train, epochs=5)
-
-model.evaluate(x_test,  y_test, verbose=2)