Use all data in training and change in data aug

app.py

@@ -7,11 +7,14 @@ import numpy as np
 
 (X_train, y_train) , (X_test, y_test) = keras.datasets.mnist.load_data()
 
+X_train = np.concatenate((X_train, X_test))
+y_train = np.concatenate((y_train, y_test))
+
 X_train = X_train / 255
 X_test = X_test / 255
 
 data_augmentation = keras.Sequential([
-    tf.keras.layers.experimental.preprocessing.RandomRotation(0.3, input_shape=(28, 28, 1)),
+    tf.keras.layers.experimental.preprocessing.RandomRotation(0.2, input_shape=(28, 28, 1)),
 ])
 
 model = models.Sequential([