Harnessing large language models (25 résultats)

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Etat : New. Print on Demand.

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PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

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HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.

HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.

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Hardback. Etat : New.

Hardback. Etat : New.

Paperback. Etat : new. Paperback. Harnessing large language models (LLMs) for enhanced business analytics changes how organizations process, interpret, and use data. These advanced AI systems utilize natural language understanding and generation, making them powerful tools for insights from data sources such as customer feedback, social media, emails, and reports. By integrating LLMs into business analytics workflows, companies can automate data interpretation, generate real-time insights, and support more informed decision-making. From summarizing complex datasets to predicting market trends and optimizing operations, LLMs redefine how businesses can analyze and leverage information, driving innovation and competitive advantage in a data-driven world. Harnessing Large Language Models for Enhanced Business Analytics delves into the transformative role of large language models (LLMs) in business analytics, bridging the gap between AI research and practical business applications by showcasing how LLMs can analyze datasets, uncover insights, predict trends, and facilitate decision-making. It examines theoretical foundations, practical applications, and future directions of LLMs in business environments. This book covers topics such as risk management, fraud detection, and data science, and is a useful resource for business owners, computer engineers, security professionals, academicians, researchers, and scientists. "This book aims to make a significant impact on both academic and professional realms by providing a comprehensive resource on leveraging LLMs for business analytics"-- Provided by publisher. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Etat : new. Hardcover. Harnessing large language models (LLMs) for enhanced business analytics changes how organizations process, interpret, and use data. These advanced AI systems utilize natural language understanding and generation, making them powerful tools for insights from data sources such as customer feedback, social media, emails, and reports. By integrating LLMs into business analytics workflows, companies can automate data interpretation, generate real-time insights, and support more informed decision-making. From summarizing complex datasets to predicting market trends and optimizing operations, LLMs redefine how businesses can analyze and leverage information, driving innovation and competitive advantage in a data-driven world. Harnessing Large Language Models for Enhanced Business Analytics delves into the transformative role of large language models (LLMs) in business analytics, bridging the gap between AI research and practical business applications by showcasing how LLMs can analyze datasets, uncover insights, predict trends, and facilitate decision-making. It examines theoretical foundations, practical applications, and future directions of LLMs in business environments. This book covers topics such as risk management, fraud detection, and data science, and is a useful resource for business owners, computer engineers, security professionals, academicians, researchers, and scientists. "This book aims to make a significant impact on both academic and professional realms by providing a comprehensive resource on leveraging LLMs for business analytics"-- Provided by publisher. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Etat : new. Paperback. Harnessing large language models (LLMs) for enhanced business analytics changes how organizations process, interpret, and use data. These advanced AI systems utilize natural language understanding and generation, making them powerful tools for insights from data sources such as customer feedback, social media, emails, and reports. By integrating LLMs into business analytics workflows, companies can automate data interpretation, generate real-time insights, and support more informed decision-making. From summarizing complex datasets to predicting market trends and optimizing operations, LLMs redefine how businesses can analyze and leverage information, driving innovation and competitive advantage in a data-driven world. Harnessing Large Language Models for Enhanced Business Analytics delves into the transformative role of large language models (LLMs) in business analytics, bridging the gap between AI research and practical business applications by showcasing how LLMs can analyze datasets, uncover insights, predict trends, and facilitate decision-making. It examines theoretical foundations, practical applications, and future directions of LLMs in business environments. This book covers topics such as risk management, fraud detection, and data science, and is a useful resource for business owners, computer engineers, security professionals, academicians, researchers, and scientists. "This book aims to make a significant impact on both academic and professional realms by providing a comprehensive resource on leveraging LLMs for business analytics"-- Provided by publisher. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Etat : new. Hardcover. Harnessing large language models (LLMs) for enhanced business analytics changes how organizations process, interpret, and use data. These advanced AI systems utilize natural language understanding and generation, making them powerful tools for insights from data sources such as customer feedback, social media, emails, and reports. By integrating LLMs into business analytics workflows, companies can automate data interpretation, generate real-time insights, and support more informed decision-making. From summarizing complex datasets to predicting market trends and optimizing operations, LLMs redefine how businesses can analyze and leverage information, driving innovation and competitive advantage in a data-driven world. Harnessing Large Language Models for Enhanced Business Analytics delves into the transformative role of large language models (LLMs) in business analytics, bridging the gap between AI research and practical business applications by showcasing how LLMs can analyze datasets, uncover insights, predict trends, and facilitate decision-making. It examines theoretical foundations, practical applications, and future directions of LLMs in business environments. This book covers topics such as risk management, fraud detection, and data science, and is a useful resource for business owners, computer engineers, security professionals, academicians, researchers, and scientists. "This book aims to make a significant impact on both academic and professional realms by providing a comprehensive resource on leveraging LLMs for business analytics"-- Provided by publisher. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Etat : new. Paperback. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.

Taschenbuch. Etat : Neu. Harnessing Large Language Models for Enhanced Business Analytics | Fabio Perez Marzullo | Taschenbuch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798369366912 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …

Hardcover. Etat : new. Hardcover. Harnessing large language models (LLMs) for enhanced business analytics changes how organizations process, interpret, and use data. These advanced AI systems utilize natural language understanding and generation, making them powerful tools for insights from data sources such as customer feedback, social media, emails, and reports. By integrating LLMs into business analytics workflows, companies can automate data interpretation, generate real-time insights, and support more informed decision-making. From summarizing complex datasets to predicting market trends and optimizing operations, LLMs redefine how businesses can analyze and leverage information, driving innovation and competitive advantage in a data-driven world. Harnessing Large Language Models for Enhanced Business Analytics delves into the transformative role of large language models (LLMs) in business analytics, bridging the gap between AI research and practical business applications by showcasing how LLMs can analyze datasets, uncover insights, predict trends, and facilitate decision-making. It examines theoretical foundations, practical applications, and future directions of LLMs in business environments. This book covers topics such as risk management, fraud detection, and data science, and is a useful resource for business owners, computer engineers, security professionals, academicians, researchers, and scientists. "This book aims to make a significant impact on both academic and professional realms by providing a comprehensive resource on leveraging LLMs for business analytics"-- Provided by publisher. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Buch. Etat : Neu. Harnessing Large Language Models for Enhanced Business Analytics | Fabio Perez Marzullo | Buch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798369366905 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.