Author Description

This book covers the wealth of modern techniques in time series modeling. It presents the key concepts and provides the theoretical motivations and code examples. It organizes the techniques according to the data science process: data preparation, model specification, modeling, and forecasting. It is therefore approachable for data science professionals who want to get hands-on practice on cutting-edge techniques in time series modeling, forecasting, and anomaly detection. This book is certainly suitable for students who want to advance in time series modeling and fraud detection.