temporal and images multiple feature scaling techniques are also coveredwhich are useful to tone down the scale and magnitude of features before modeling finallywe cover feature selection techniques in detail with emphasis on the three different strategies of feature selection namely filterwrapperand embedded methods special sections on dimensionality reduction and automated feature extraction using deep learning have also been included since they have gained lot of prominence in both research as well as the industry want to conclude this by leaving you with the following quote by peter norvigrenowned computer scientist and director at googlewhich should reinforce the importance of feature engineering "more data beats clever algorithmsbut better data beats more data --peter norvig