title: When to apply Data whitening
body: <p>Data Whitening (features scaling and mean normalization) is very useful when we use features that represent different characteristics and are on very different scales (eg number of rooms in a house and house price). </p>
  
  <p>What about the case when the features represent "similar variables" but are on a very different scale?
  Let's suppose for instance that we have a matrix representing the numbers of different species at different moments in an environment and we want to regroup these species into groups (say, for example, to prove that mosquitoes and birds populations are very correlated). In this example, the number of mosquitoes is much bigger than the one of birds (say ten or a hundred times). Is it a good idea to whiten this data?</p>