Feature engineering

Feature engineering plays a vital role in making machine learning algorithms work and, if carried out properly, it enhances the predictive ability of machine learning algorithms. In other words, feature engineering is the process of extracting existing features or creating new features from the raw data using domain knowledge, the context of the problem, or specialized techniques that result in more accurate predictive models. This is an activity where domain knowledge and creativity play a very important role. This is an important process, which can significantly improve the performance of our predictive models. The more context you have about a problem, the better your ability to create new and useful features. Basically, the feature engineering process converts the features into input values that algorithms can understand.
There are various ways of implementing...