title: feature scaling and intercept
body: <p>it is a beginner question but I have a dataset of two features house sizes and number of bedrooms, So I'm working on Octave; So basically I try to do a feature scaling but as in the Design Matrix I added A column of ones (for tetha0) So I try to do a mean normalisation : (x- mean(x)/std(x) 
  but in the columns of one obviously the mean is 1 since there is only 1 in every line So when I do this the intercept colum is set to 0 :</p>
  
  <pre><code> mu = mean(X)
  mu =
  
    1.0000   2000.6809      3.1702
  
   votric = X - mu
  votric =
  
    0.00000    103.31915     -0.17021
    0.00000   -400.68085     -0.17021
    0.00000    399.31915     -0.17021
    0.00000   -584.68085     -1.17021
    0.00000    999.31915      0.82979
  </code></pre>
  
  <p>So the first column shouldn't be left out of the mean normalization ?</p>