ABSTRACT
This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book provides a systematic review of the main techniques for feature representations for text data. It presents a hierarchy of feature representations for image data, starting with classic, handcrafted features. The book provides an overview of a vast literature of representations and analysis methods for time series. It provides an overview of feature engineering for streaming data, with a focus on streaming feature construction and selection. The book discusses ways to algorithmically tackle the problem of feature engineering using transformation functions in the context of supervised learning. It reviews various classical and popular deep learning algorithms and explains how they can be used for feature representation learning. The book considers feature engineering for social bot detection in the context of social media. It presents studies concerning feature engineering for twitter-based applications.
