import tensorflow as tf [...] model = tf.keras.Sequential([ tf.keras.layers.Dense(64, activation=tf.nn.relu, input_shape=[len(train_dataset.keys())]), tf.keras.layers.Dense(64, activation=tf.nn.relu), tf.keras.layers.Dense(1) ]) optimizer = tf.keras.optimizers.RMSprop(0.001) model.compile(loss='mean_squared_error', optimizer=optimizer, metrics=['mean_absolute_error', 'mean_squared_error'])