The book introduces popular forecasting methods and approaches used in a variety of business applications. The book offers clear explanations, practical examples, and end-of-chapter exercises and cases.

The book is a summary of a time series forecasting competition that was held a number of years ago.

Leverage Cloud platforms with Azure Time Series Insights and AWS Forecast Components for Deep learning Modeling ... Non - Parametric Time Series ( NPTS ) , and from the " Deep Learning " algorithm family , it includes DeepAR + and ...

This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis.

The need for this book is based on the recent developments in nonlinear time series analysis, statistical learning, dynamic systems and advanced computational methods.

The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.

This is the first book that integrates useful parametric and nonparametric techniques with time series modeling and prediction, the two important goals of time series analysis.

The book introduces popular forecasting methods and approaches used in a variety of business applications. The book offers clear explanations, practical examples, and end-of-chapter exercises and cases.

This is an introduction to time series that emphasizes methods and analysis of data sets.

The book presents methodologies for time series analysis in a simplified, example-based approach.