Feature selection using Wrapper methods in Python

In today's era of Big data and IoT, we are easily loaded with rich datasets having extremely high dimensions. In order to perform any machine learning task or to get insights from such high dimensional data, feature selection becomes very important. Hence, it gives an indispensable need to perform feature selection. Feature selection is very crucial and must component in machine learning and data science workflows especially while dealing with high dimensional datasets. As the name suggests, it is a process of selecting the most significant and relevant features from a vast set of features in the given dataset.