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choose the correct pairing. X _ train = X _ train.reshape ( ( X _ train.shape [ 0 ] , 2 8 , 2 8

choose the correct pairing.
X_train = X_train.reshape((X_train.shape[0],28,28,1))
X_train = X_train.astype('float32')/255.0
y_train_encoded = tf.keras.utils.to_categorical(y_train)
model = Sequential()
model.add(Conv2D(64,(3,3), activation='relu', padding="same", input_shape=(28,28,1)))
model.add(MaxPooling2D((2,2), padding = 'same'))
model.add(Flatten())
model.add(Dense(100, activation='relu'))
model.add(Dense(10, activation='softmax'))

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