title: How important is image mean subtraction in convnets?
body: <p>So I've read that mean subtraction is very important for images since it zero-centers the data.
  From <a href="http://cs231n.github.io/neural-networks-2/" rel="nofollow noreferrer">this</a> lecture.</p>
  
  <blockquote>
    <p>However, it is very important to zero-center the data, and it is common to see normalization of every pixel as well.</p>
  </blockquote>
  
  <p>Yet I've never seen this in practice in all the MNIST and cat/dog classification tutorials out there. Is it really that important? What would happen if you did not zero-center the data? Can anyone point to me a tutorial notebook, preferably in Tensorflow, that shows mean subtraction being done?  </p>