this is the code from the TensorFlow website, but doesn't explain well,
normalization_layer = tf.keras.layers.Rescaling(1./255)
train_data = train_data.map(lambda x, y: (normalization_layer(x), y)) # Where x—images, y—labels.
i know what is the goal of this code which is to normalize data and make it between 0 and 1 instead of 0 to 255, but I need to understand what does lambda means here.