python import tensorflow as tf from sklearn.preprocessing import MinMaxScaler from sklearn.model_selection import train_test_split data = tf.keras.datasets.mnist.load_data() (X_train, y_train), (X_test, y_test) = data scaler = MinMaxScaler(feature_range=(0, 1)) X_train_scaled = scaler.fit_transform(X_train.reshape(-1, 28 * 28)) X_test_scaled = scaler.transform(X_test.reshape(-1, 28 * 28)) X_train_final, X_val, y_train_final, y_val = train_test_split(X_train_scaled, y_train, test_size=0.2, random_state=42)