Articoli correlati a Time Series for Data Science: Analysis and Forecasting
Sinossi
Data Science students and practitioners want to find a forecast that “works” and don’t want to be constrained to a single forecasting strategy, Time Series for Data Science: Analysis and Forecasting discusses techniques of ensemble modelling for combining information from several strategies. Covering time series regression models, exponential smoothing, Holt-Winters forecasting, and Neural Networks. It places a particular emphasis on classical ARMA and ARIMA models that is often lacking from other textbooks on the subject.
This book is an accessible guide that doesn’t require a background in calculus to be engaging but does not shy away from deeper explanations of the techniques discussed.
Features:
- Provides a thorough coverage and comparison of a wide array of time series models and methods: Exponential Smoothing, Holt Winters, ARMA and ARIMA, deep learning models including RNNs, LSTMs, GRUs, and ensemble models composed of combinations of these models.
- Introduces the factor table representation of ARMA and ARIMA models. This representation is not available in any other book at this level and is extremely useful in both practice and pedagogy.
- Uses real world examples that can be readily found via web links from sources such as the US Bureau of Statistics, Department of Transportation and the World Bank.
- There is an accompanying R package that is easy to use and requires little or no previous R experience. The package implements the wide variety of models and methods presented in the book and has tremendous pedagogical use.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sull?autore
Wayne Woodward, Bivin Sadler, Stephen Robertson
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Compra nuovo
Visualizza questo articolo
EUR 56,09
EUR 7,65 per la spedizione in U.S.A.
Destinazione, tempi e costi
Risultati della ricerca per Time Series for Data Science: Analysis and Forecasting
Foto dell'editore
Time Series for Data Science (Chapman & Hall/CRC Texts in Statistical Science)
Da: Best Price, Torrance, CA, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. SUPER FAST SHIPPING. Codice articolo 9780367543891
Quantità: 1 disponibili
Foto dell'editore
Time Series for Data Science : Analysis and Forecasting
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo 47617209-n
Quantità: Più di 20 disponibili
Foto dell'editore
Practical time series analysis for data science
Da: Majestic Books, Hounslow, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. pages cm. Codice articolo 398668548
Quantità: 3 disponibili
Foto dell'editore
Time Series for Data Science : Analysis and Forecasting
Editore:
Chapman and Hall/CRC, 2024
ISBN 10: 0367543893
ISBN 13: 9780367543891
Antico o usato
Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: As New. Unread book in perfect condition. Codice articolo 47617209
Quantità: Più di 20 disponibili
Foto dell'editore
Time Series for Data Science: Analysis and Forecasting
Editore:
Taylor & Francis Ltd, 2024
ISBN 10: 0367543893
ISBN 13: 9780367543891
Nuovo
Paperback / softback
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
Valutazione del venditore 5 su 5 stelle
Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days. 453. Codice articolo B9780367543891
Quantità: 1 disponibili
Foto dell'editore
Time Series for Data Science (Paperback)
Da: Grand Eagle Retail, Mason, OH, U.S.A.
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: new. Paperback. Data Science students and practitioners want to find a forecast that works and dont want to be constrained to a single forecasting strategy, Time Series for Data Science: Analysis and Forecasting discusses techniques of ensemble modelling for combining information from several strategies. Covering time series regression models, exponential smoothing, Holt-Winters forecasting, and Neural Networks. It places a particular emphasis on classical ARMA and ARIMA models that is often lacking from other textbooks on the subject.This book is an accessible guide that doesnt require a background in calculus to be engaging but does not shy away from deeper explanations of the techniques discussed.Features:Provides a thorough coverage and comparison of a wide array of time series models and methods: Exponential Smoothing, Holt Winters, ARMA and ARIMA, deep learning models including RNNs, LSTMs, GRUs, and ensemble models composed of combinations of these models.Introduces the factor table representation of ARMA and ARIMA models. This representation is not available in any other book at this level and is extremely useful in both practice and pedagogy.Uses real world examples that can be readily found via web links from sources such as the US Bureau of Statistics, Department of Transportation and the World Bank.There is an accompanying R package that is easy to use and requires little or no previous R experience. The package implements the wide variety of models and methods presented in the book and has tremendous pedagogical use. Practical Time Series Analysis for Data Science is an accessible guide that doesnt require a background in calculus to be engaging but does not shy away from deeper explanations of the techniques discussed. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9780367543891
Quantità: 1 disponibili
Foto dell'editore
Time Series for Data Science
Print on DemandDa: PBShop.store US, Wood Dale, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L0-9780367543891
Quantità: Più di 20 disponibili
Foto dell'editore
Time Series for Data Science
Print on DemandDa: PBShop.store UK, Fairford, GLOS, Regno Unito
Valutazione del venditore 5 su 5 stelle
PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L0-9780367543891
Quantità: Più di 20 disponibili
Foto dell'editore
Practical time series analysis for data science
Da: Books Puddle, New York, NY, U.S.A.
Valutazione del venditore 4 su 5 stelle
Condizione: New. pages cm First edition Includes bibliographical references and index. Codice articolo 26397708507
Quantità: 3 disponibili
Immagini fornite dal venditore
Time Series for Data Science
Editore:
Chapman And Hall/CRC Mai 2024, 2024
ISBN 10: 0367543893
ISBN 13: 9780367543891
Nuovo
Taschenbuch
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data Science students and practitioners want to find a forecast that 'works' and don't want to be constrained to a single forecasting strategy, Time Series for Data Science: Analysis and Forecasting discusses techniques of ensemble modelling for combining information from several strategies. Covering time series regression models, exponential smoothing, Holt-Winters forecasting, and Neural Networks. It places a particular emphasis on classical ARMA and ARIMA models that is often lacking from other textbooks on the subject.This book is an accessible guide that doesn't require a background in calculus to be engaging but does not shy away from deeper explanations of the techniques discussed.Features:Provides a thorough coverage and comparison of a wide array of time series models and methods: Exponential Smoothing, Holt Winters, ARMA and ARIMA, deep learning models including RNNs, LSTMs, GRUs, and ensemble models composed of combinations of these models.Introduces the factor table representation of ARMA and ARIMA models. This representation is not available in any other book at this level and is extremely useful in both practice and pedagogy.Uses real world examples that can be readily found via web links from sources such as the US Bureau of Statistics, Department of Transportation and the World Bank.There is an accompanying R package that is easy to use and requires little or no previous R experience. The package implements the wide variety of models and methods presented in the book and has tremendous pedagogical use. 530 pp. Englisch. Codice articolo 9780367543891
Quantità: 2 disponibili