title: References for data normalization
body: <p>What are the best practices on normalizing data (not sure if that is the right term) for NNs and other machine learning algorithms?  What I mean is how you represent data to the NN/algo.  </p>
  
  <p>For instance, how do you represent a store code?  Store 555 isn't greater or less than 554, it is just a classification. Do NNs/algo models just filter that out on their own or do you need to prod them into making a classification rather mathematical distinction?</p>
  
  <p>Thanks for any help in directing me to appropriate information.  I am obviously new to this.</p>
  
  <p><strong>EDIT</strong>: Thanks to everyone for the answers.  I have been digging through quite a few data mining books and while I have found a few that spend a chapter or two on the topic of data pre-processing I am a little surprised at how most gloss over it entirely.  Thanks again.</p>