Isbn: 9786206766896 - wine quality analysis using artificial intelligence and machine learning: ai and ml approach (5 risultati)

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    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2023

      6206766896 / 9786206766896

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      Da: preigu, Osnabrück, Germaniapreigu

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      EUR 37,50

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      Taschenbuch. Condizione: Neu. Wine Quality Analysis Using Artificial Intelligence and Machine Learning | AI AND ML Approach | Pankaj Agarkar (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206766896 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing Aug 2023, 2023

      6206766896 / 9786206766896

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      Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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      EUR 43,90

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      Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The wine quality is important for the consumers as well as for the wine industry. The traditional (expert wine tester) way of measuring wine quality might be expensive and time-consuming. Nowadays, machine learning models are foremost tools to replace human intervention. As a sub field of Artificial Intelligence (AI), Machine Learning (ML) aims to understand the structure of the data and fit it into models, which later can be used on unseen data to achieve the desired task. Machine Learning has been widely used in various sectors such as Businesses, Medical, and Astrophysics to name a few and many other scientific problems. Inspired by success of Artificial Intelligence in various different sectors here, we can use it for wine quality prediction based on various physicochemical properties of wine. Among various machine learning methods, we analyze the performance of Extremely randomized trees (Extra trees), Extreme Gradient Boosting (XG Boost) and Light gradient-boosting machine (Light GBM) ensemble ML methods. This work demonstrates how statistical data analysis can be used to identify the components that mainly control the wine quality prior to the production. 84 pp. Englisch.

    • Lingua: Inglese

      Editore: LAP Lambert Academic Publishing, 2023

      6206766896 / 9786206766896

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      Da: moluna, Greven, Germaniamoluna

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      EUR 37,23

      EUR 48,99 spedizione 
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      Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The wine quality is important for the consumers as well as for the wine industry. The traditional (expert wine tester) way of measuring wine quality might be expensive and time-consuming. Nowadays, machine learning models are foremost tools to replace human.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2023

      6206766896 / 9786206766896

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      • Print on Demand

      Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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      EUR 64,04

      EUR 30,50 spedizione 
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      Quantità: 1 disponibili

      Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The wine quality is important for the consumers as well as for the wine industry. The traditional (expert wine tester) way of measuring wine quality might be expensive and time-consuming. Nowadays, machine learning models are foremost tools to replace human intervention. As a sub field of Artificial Intelligence (AI), Machine Learning (ML) aims to understand the structure of the data and fit it into models, which later can be used on unseen data to achieve the desired task. Machine Learning has been widely used in various sectors such as Businesses, Medical, and Astrophysics to name a few and many other scientific problems. Inspired by success of Artificial Intelligence in various different sectors here, we can use it for wine quality prediction based on various physicochemical properties of wine. Among various machine learning methods, we analyze the performance of Extremely randomized trees (Extra trees), Extreme Gradient Boosting (XG Boost) and Light gradient-boosting machine (Light GBM) ensemble ML methods. This work demonstrates how statistical data analysis can be used to identify the components that mainly control the wine quality prior to the production.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing Aug 2023, 2023

      6206766896 / 9786206766896

      • Brossura
      • Print on Demand

      Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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      Condizione: Nuovo

      EUR 43,90

      EUR 60,00 spedizione 
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      Quantità: 1 disponibili

      Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The wine quality is important for the consumers as well as for the wine industry. The traditional (expert wine tester) way of measuring wine quality might be expensive and time-consuming. Nowadays, machine learning models are foremost tools to replace human intervention. As a sub field of Artificial Intelligence (AI), Machine Learning (ML) aims to understand the structure of the data and fit it into models, which later can be used on unseen data to achieve the desired task. Machine Learning has been widely used in various sectors such as Businesses, Medical, and Astrophysics to name a few and many other scientific problems. Inspired by success of Artificial Intelligence in various different sectors here, we can use it for wine quality prediction based on various physicochemical properties of wine. Among various machine learning methods, we analyze the performance of Extremely randomized trees (Extra trees), Extreme Gradient Boosting (XG Boost) and Light gradient-boosting machine (Light GBM) ensemble ML methods. This work demonstrates how statistical data analysis can be used to identify the components that mainly control the wine quality prior to the production.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch.