Feature extraction refers to the procedure of converting raw data into a collection of features. These features are the pertinent characteristics or attributes of the data, capable of representing it in a more meaningful and effective manner. In the realm of machine learning, feature extraction is a vital step within data pre-processing. It serves to decrease the dimensionality of the data and distill only the relevant information that is beneficial for training a machine-learning model.
