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Practical Time Series Forecasting with R

A Hands-On Guide [2nd Edition]

By: Galit Shmueli,Kenneth C. Lichtendahl Jr.

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Practical Time Series Forecasting with R

A Hands-On Guide [2nd Edition]

By: Galit Shmueli,Kenneth C. Lichtendahl Jr.

Practical Time Series Forecasting with R: A Hands-On Guide, Second Edition provides an applied approach to time-series forecasting. Forecasting is an essential component of predictive analytics. 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. Readers will learn to use forecasting methods using the free open-source R software to develop effective forecasting solutions that extract business value from time-series data. Featuring improved organization and new material, the Second Edition also includes: - Popular forecasting methods including smoothing algorithms, regression models, and neural networks - A practical approach to evaluating the performance of forecasting solutions - A business-analytics exposition focused on linking time-series forecasting to business goals - Guided cases for integrating the acquired knowledge using real data* End-of-chapter problems to facilitate active learning - A companion site with data sets, R code, learning resources, and instructor materials (solutions to exercises, case studies) - Globally-available textbook, available in both softcover and Kindle formats Practical Time Series Forecasting with R: A Hands-On Guide, Second Edition is the perfect textbook for upper-undergraduate, graduate and MBA-level courses as well as professional programs in data science and business analytics. The book is also designed for practitioners in the fields of operations research, supply chain management, marketing, economics, finance and management. For more information, visit forecastingbook.com

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Page Count

232

Publisher

Axelrod Schnall Publishers

Published Date

ISBN 10

0997847913

ISBN 13

9780997847918

Data Mining for Business Analytics

Concepts, Techniques, and Applications in R

By: Galit Shmueli,Peter C. Bruce,Inbal Yahav,Nitin R. Patel,Kenneth C. Lichtendahl, Jr.

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Data Mining for Business Analytics

Concepts, Techniques, and Applications in R

By: Galit Shmueli,Peter C. Bruce,Inbal Yahav,Nitin R. Patel,Kenneth C. Lichtendahl, Jr.

Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and methods, using R software for illustration Readers will learn how to implement a variety of popular data mining algorithms in R (a free and open-source software) to tackle business problems and opportunities. This is the fifth version of this successful text, and the first using R. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: Two new co-authors, Inbal Yahav and Casey Lichtendahl, who bring both expertise teaching business analytics courses using R, and data mining consulting experience in business and government Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions www.dataminingbook.com Data Mining for Business Analytics: Concepts, Techniques, and Applications in R is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology.

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Page Count

576

Publisher

John Wiley & Sons

Published Date

ISBN 10

1118879333

ISBN 13

9781118879337