title: Normalize numpy ndarray data
body: <p>My data is numpy ndarray with shape(2,3,4) following this: 
  I've try to normalize 0-1 scale for each column through sklearn normalization. </p>
  
  <pre><code>from sklearn.preprocessing import normalize  
  
  x = np.array([[[1, 2, 3, 4],
        [2, 2, 3, 4],
        [3, 2, 3, 4]],
        [[4, 2, 3, 4],
        [5, 2, 3, 4],
        [6, 2, 3, 4]]])
  
  x.shape ==&gt; ( 2,3,4) 
  
  x = normalize(x, norm='max', axis=0, ) 
  </code></pre>
  
  <p>However, I catch the error :</p>
  
  <pre><code>ValueError: Found array with dim 3. the normalize function expected &lt;= 2.
  </code></pre>
  
  <p>How do I solve this problem? </p>
  
  <p>Thank you. </p>