Feature scaling and normalization are important steps in data preprocessing. They help prepare data for machine learning algorithms by ensuring that numerical values are on a similar scale. When features have very different ranges, some algorithms may give more importance to larger values and ignore smaller ones. This can influence the precision and functionality of a model. As machine learning...