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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 47617209
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Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Paperback / softback. Etat : New. New copy - Usually dispatched within 4 working days. N° de réf. du vendeur B9780367543891
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9780367543891_new
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 47617209-n
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Vendeur : Grand Eagle Retail, Wilmington, DE, Etats-Unis
Paperback. Etat : 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. N° de réf. du vendeur 9780367543891
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 506 pages. In Stock. This item is printed on demand. N° de réf. du vendeur __0367543893
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Vendeur : Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlande
Etat : New. N° de réf. du vendeur V9780367543891
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : 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. 528 pp. Englisch. N° de réf. du vendeur 9780367543891
Quantité disponible : 2 disponible(s)
Vendeur : GreatBookPricesUK, Castle Donington, DERBY, Royaume-Uni
Etat : New. N° de réf. du vendeur 47617209-n
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Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. N° de réf. du vendeur C9780367543891
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