When should I do feature scaling or Normalisation in Machine learning? : I have a training feature set consisting of 92 features. Out of which 91 features are boolean value 1 or 0. But 1 feature is numerical vary from 3-2000. Will it be good if I do feature scaling on my 92nd feature?

If Yes, what are the best possible ways to do it?