Update model.py

model.py

@@ -86,6 +86,9 @@ val_spectrogram_ds = val_spectrogram_ds.cache().prefetch(tf.data.AUTOTUNE)
 test_spectrogram_ds = test_spectrogram_ds.cache().prefetch(tf.data.AUTOTUNE)
 
 
+#use a simple convolutional neural network (CNN), since you have transformed the audio files into spectrogram images
+#tf.keras.layers.Resizing: to downsample the input to enable the model to train faster.
+#tf.keras.layers.Normalization: to normalize each pixel in the image based on its mean and standard deviation
 input_shape = example_spectrograms.shape[1:]
 print('Input shape:', input_shape)
 num_labels = len(label_names)