This book examines the design of an automated system for financial time series forecasting. It explores the level of automation which can be achieved by a system for modelling a given financial time series with the minimum of human intervention. It aims t
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
This book examines the design of an automated system for financial time series forecasting. It explores the level of automation which can be achieved by a system for modelling a given financial time series with the minimum of human intervention. It aims t
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : Anybook.com, Lincoln, Royaume-Uni
Etat : Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In fair condition, suitable as a study copy. Library sticker on front cover. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,450grams, ISBN:9783540760986. N° de réf. du vendeur 4333753
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Vendeur : Michael Knight, Bookseller, Forest Grove, OR, Etats-Unis
paperback. Etat : Very Good. Paperback. Clean and solid. Ships from a smoke-free home. N° de réf. du vendeur M22-0000-112-C5-000
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Vendeur : NEPO UG, Rüsselsheim am Main, Allemagne
Taschenbuch. Etat : Gut. 227 Seiten ex Library Book aus einer wissenschaftlichen Bibliothek Sprache: Englisch Gewicht in Gramm: 341. N° de réf. du vendeur 277762
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Vendeur : Buchpark, Trebbin, Allemagne
Etat : Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | A fundamental objective of Artificial Intelligence (AI) is the creation of in telligent computer programs. In more modest terms AI is simply con cerned with expanding the repertoire of computer applications into new domains and to new levels of efficiency. The motivation for this effort comes from many sources. At a practical level there is always a demand for achieving things in more efficient ways. Equally, there is the technical challenge of building programs that allow a machine to do something a machine has never done before. Both of these desires are contained within AI and both provide the inspirational force behind its development. In terms of satisfying both of these desires there can be no better example than machine learning. Machines that can learn have an in-built effi ciency. The same software can be applied in many applications and in many circumstances. The machine can adapt its behaviour so as to meet the demands of new, or changing, environments without the need for costly re-programming. In addition, a machine that can learn can be ap plied in new domains with the genuine potential for innovation. In this sense a machine that can learn can be applied in areas where little is known about possible causal relationships, and even in circumstances where causal relationships are judged not to exist. This last aspect is of major significance when considering machine learning as applied to fi nancial forecasting. N° de réf. du vendeur 18740/2
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9783540760986_new
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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 -A fundamental objective of Artificial Intelligence (AI) is the creation of in telligent computer programs. In more modest terms AI is simply con cerned with expanding the repertoire of computer applications into new domains and to new levels of efficiency. The motivation for this effort comes from many sources. At a practical level there is always a demand for achieving things in more efficient ways. Equally, there is the technical challenge of building programs that allow a machine to do something a machine has never done before. Both of these desires are contained within AI and both provide the inspirational force behind its development. In terms of satisfying both of these desires there can be no better example than machine learning. Machines that can learn have an in-built effi ciency. The same software can be applied in many applications and in many circumstances. The machine can adapt its behaviour so as to meet the demands of new, or changing, environments without the need for costly re-programming. In addition, a machine that can learn can be ap plied in new domains with the genuine potential for innovation. In this sense a machine that can learn can be applied in areas where little is known about possible causal relationships, and even in circumstances where causal relationships are judged not to exist. This last aspect is of major significance when considering machine learning as applied to fi nancial forecasting. 240 pp. Englisch. N° de réf. du vendeur 9783540760986
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Vendeur : moluna, Greven, Allemagne
Etat : New. N° de réf. du vendeur 4900365
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Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. pp. 240. N° de réf. du vendeur 2658569700
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Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand pp. 240 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam. N° de réf. du vendeur 50990139
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Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Etat : New. PRINT ON DEMAND pp. 240. N° de réf. du vendeur 1858569710
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