title: How do Encoder/Decoder models learn in Deep Learning?
body: <p>After learning a bit about encoder/decoder models in deep learning (mostly in Keras), i still cannot understand where the learning takes place.</p>
  
  <p>Does the encoder just create the feature map and then the decoder tries to get as close as possible as the result with BackProp, or does the encoder learn as well when the model is trained?</p>
  
  <p>One last question: if i understood correctly, the filters are the equivalent of the nodes in a classic machine learning model, changing its weights to learn, am i right?</p>