Conv2D-Conv2D-MaxPooling2D import tensorflow as tf mnist=tf.keras.datasets.fashion_mnist (x_train, y_train),(x_test, y_test)=mnist.load_data() x_train, x_test = x_train / 255.0, x_test / 255.0 x_train = x_train.reshape((60000, 28, 28, 1)) x_test = x_test.reshape((10000, 28, 28, 1)) model = tf.keras.Sequential([ tf.keras.layers.InputLayer(input_shape=(28,28,1)), tf.keras.layers.Conv2D(32,(3,3),ac..