title: What is the difference between steps and epochs in TensorFlow?
body: <p>In most of the models, there is a <em>steps</em> parameter indicating the <em>number of steps to run over data</em>. But yet I see in most practical usage, we also execute the fit function N <em>epochs</em>. </p>
  
  <p>What is the difference between running 1000 steps with 1 epoch and running 100 steps with 10 epoch? Which one is better in practice? Any logic changes between consecutive epochs? Data shuffling?</p>