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Natural Language Analytics with Generative Large-Language Models: A Practical Approach with Ollama and Open-Source LLMs (SpringerBriefs in Computer Science) - Tapa blanda
- EditorialSpringer-Verlag GmbH
- Año de publicación2025
- ISBN 10 303176630X
- ISBN 13 9783031766305
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas100
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Natural Language Analytics with Generative Large-Language Models (Paperback)
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Springer International Publishing AG, Cham, 2025
ISBN 10: 303176630X
ISBN 13: 9783031766305
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Paperback. Condición: new. Paperback. This book explores the application of generative Large Language Models (LLMs) for extracting and analyzing data from natural language artefacts. Unlike traditional uses of LLMs, such as translation and summarization, this book focuses on utilizing these models to convert unstructured text into data that can be processed through the data science pipeline to generate actionable insights.The content is designed for professionals in diverse fields including cognitive science, linguistics, management, and information systems. It combines insights from both industry and academia to provide a comprehensive understanding of how LLMs can be effectively used for natural language analytics (NLA). The book details practical methodologies for implementing LLMs locally using open-source tools, ensuring data privacy and feasibility without the need for expensive infrastructure.Key topics include interpretant, mindset and cultural analysis, emphasizing the use of LLMs to derive soft dataqualitative information crucial for nuanced decision-making. The text also outlines the technical aspects of LLMs, including their architecture, token embeddings, and the differences between encoder-based and decoder-based models. By providing a case study and practical examples, the authors show how LLMs can be used to meet various analytical needs, making this book a valuable resource for anyone looking to integrate advanced natural language processing techniques into their data analysis workflows. This book explores the application of generative Large Language Models (LLMs) for extracting and analyzing data from natural language artefacts. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783031766305
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Natural Language Analytics with Generative Large-Language Models
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Springer, Berlin, Springer Nature Switzerland, Springer, 2025
ISBN 10: 303176630X
ISBN 13: 9783031766305
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book explores the application of generative Large Language Models (LLMs) for extracting and analyzing data from natural language artefacts. Unlike traditional uses of LLMs, such as translation and summarization, this book focuses on utilizing these models to convert unstructured text into data that can be processed through the data science pipeline to generate actionable insights.The content is designed for professionals in diverse fields including cognitive science, linguistics, management, and information systems. It combines insights from both industry and academia to provide a comprehensive understanding of how LLMs can be effectively used for natural language analytics (NLA). The book details practical methodologies for implementing LLMs locally using open-source tools, ensuring data privacy and feasibility without the need for expensive infrastructure.Key topics include interpretant, mindset and cultural analysis, emphasizing the use of LLMs to derive soft data-qualitative information crucial for nuanced decision-making. The text also outlines the technical aspects of LLMs, including their architecture, token embeddings, and the differences between encoder-based and decoder-based models. By providing a case study and practical examples, the authors show how LLMs can be used to meet various analytical needs, making this book a valuable resource for anyone looking to integrate advanced natural language processing techniques into their data analysis workflows. 84 pp. Englisch. Nº de ref. del artículo: 9783031766305
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Natural Language Analytics with Generative Large-Language Models : A Practical Approach with Ollama and Open-Source LLMs
Publicado por
Springer Nature Switzerland, Springer International Publishing, 2025
ISBN 10: 303176630X
ISBN 13: 9783031766305
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explores the application of generative Large Language Models (LLMs) for extracting and analyzing data from natural language artefacts. Unlike traditional uses of LLMs, such as translation and summarization, this book focuses on utilizing these models to convert unstructured text into data that can be processed through the data science pipeline to generate actionable insights.The content is designed for professionals in diverse fields including cognitive science, linguistics, management, and information systems. It combines insights from both industry and academia to provide a comprehensive understanding of how LLMs can be effectively used for natural language analytics (NLA). The book details practical methodologies for implementing LLMs locally using open-source tools, ensuring data privacy and feasibility without the need for expensive infrastructure.Key topics include interpretant, mindset and cultural analysis, emphasizing the use of LLMs to derive soft data-qualitative information crucial for nuanced decision-making. The text also outlines the technical aspects of LLMs, including their architecture, token embeddings, and the differences between encoder-based and decoder-based models. By providing a case study and practical examples, the authors show how LLMs can be used to meet various analytical needs, making this book a valuable resource for anyone looking to integrate advanced natural language processing techniques into their data analysis workflows. Nº de ref. del artículo: 9783031766305
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Natural Language Analytics with Generative Large-Language Models: A Practical Approach with Ollama and Open-source LLMs
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Condición: New. Nº de ref. del artículo: 26403510328
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Natural Language Analytics With Generative Large-language Models: A Practical Approach With Ollama and Open-source Llms
Publicado por
Springer-Nature New York Inc, 2025
ISBN 10: 303176630X
ISBN 13: 9783031766305
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Librería: Revaluation Books, Exeter, Reino Unido
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Natural Language Analytics with Generative Large-Language Models: A Practical Approach with Ollama and Open-source LLMs
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Natural Language Analytics with Generative Large-Language Models: A Practical Approach with Ollama and Open-source LLMs
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Condición: New. PRINT ON DEMAND. Nº de ref. del artículo: 18403510322
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Natural Language Analytics with Generative Large-Language Models
Publicado por
Springer Verlag GmbH, 2025
ISBN 10: 303176630X
ISBN 13: 9783031766305
Nuevo
Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Nº de ref. del artículo: 1887555904
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