title: Using embedded columns
body: <p>I'm trying to understand the TensorFlow <a href="https://www.tensorflow.org/tutorials/wide_and_deep" rel="nofollow noreferrer">tutorial</a> on wide and deep learning. The demo application creates indicator columns for categorical features with few categories (gender, education), and it creates embedded columns for categorical features with many categories (native_country, occupation). </p>
  
  <p>I don't understand embedded columns. Is there a rule that clarifies when to use embedded columns instead of indicator columns? According to the documentation, the <code>dimension</code> parameter sets the dimension of the embedding. What does that mean?</p>