python import tensorflow as tf model = tf.keras.Sequential([ tf.keras.layers.Dense(64, activation='relu', input_shape=(10,)), tf.keras.layers.Dense(64, activation='relu'), tf.keras.layers.Dense(2, activation='softmax') ]) model.compile(optimizer=tf.keras.optimizers.Adam(0.01), loss=tf.keras.losses.CategoricalCrossentropy(), metrics=['accuracy']) model.fit(x_train, y_train, epochs=10, validation_data=(x_val, y_val)) predictions = model.predict(x_test) model.save('my_model')