title: Numpy:zero mean data and standardization
body: <p>I saw in tutorial (there were no further explanation) that we can process data to zero mean with <code>x -= np.mean(x, axis=0)</code> and normalize data with <code>x /= np.std(x, axis=0)</code>. Can anyone elaborate on these two pieces on code, only thing I got from documentations is that <code>np.mean</code> calculates arithmetic mean calculates mean along specific axis and <code>np.std</code> does so for standard deviation.</p>