Modern Time Series Forecasting Techniques For Predictive Analytics and Anomaly Detection: From Classical Foundations to Cutting-Edge Applications
by Chris Kuo
This book surveys time series forecasting techniques from classical foundations to contemporary applications. It focuses on the role of forecasting in predictive analytics and anomaly detection, offering readers a broad perspective on methods for analyzing evolving data and supporting data-driven decision-making.
About This Book
Modern Time Series Forecasting Techniques For Predictive Analytics and Anomaly Detection presents an overview of time series methods used to understand and anticipate changing data.
The book connects classical forecasting foundations with modern approaches for predictive analytics and anomaly detection.
It is suited to readers seeking a broad introduction to techniques that support data-driven analysis across contemporary applications.
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