9781032978093 - concept drift in large language models: adapting the conversation di desale, ketan sanjay (7 risultati)
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Da: California Books, Miami, FL, U.S.A.California Books
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EUR 84,26
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Condizione: New.
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dr. Ketan Sanjay Desale is a distinguished researcher and educator in the field of computer science, with a specialized focus on artificial intelligence, machine learning, and concept drift detection. Holding a Ph.D. in Computer Engineering, he has built.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. Neuware - This book explores the application of the complex relationship between concept drift and cutting-edge large language models to address the problems and opportunities in navigating changing data landscapes. It discusses the theoretical basis of concept drift and its consequences for large l…anguage models, particularly the transformative power of cutting-edge models such as GPT-3.5 and GPT-4. It offers real-world case studies to observe firsthand how concept drift influences the performance of language models in a variety of circumstances, delivering valuable lessons learnt and actionable takeaways. The book is designed for professionals, AI practitioners, and scholars, focused on natural language processing, machine learning, and artificial intelligence. - Examines concept drift in AI, particularly its impact on large language models - Analyses how concept drift affects large language models and its theoretical and practical consequences - Covers detection methods and practical implementation challenges in language models - Showcases examples of concept drift in GPT models and lessons learnt from their performance - Identifies future research avenues and recommendations for practitioners tackling concept drift in large language models.
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Paperback. Condizione: new. Paperback. This book explores the application of the complex relationship between concept drift and cutting-edge large language models to address the problems and opportunities in navigating changing data landscapes. It discusses the theoretical basis of concept drift and its consequences for large la…nguage models, particularly the transformative power of cutting-edge models such as GPT-3.5 and GPT-4. It offers real-world case studies to observe firsthand how concept drift influences the performance of language models in a variety of circumstances, delivering valuable lessons learnt and actionable takeaways. The book is designed for professionals, AI practitioners, and scholars, focused on natural language processing, machine learning, and artificial intelligence.Examines concept drift in AI, particularly its impact on large language modelsAnalyses how concept drift affects large language models and its theoretical and practical consequencesCovers detection methods and practical implementation challenges in language modelsShowcases examples of concept drift in GPT models and lessons learnt from their performanceIdentifies future research avenues and recommendations for practitioners tackling concept drift in large language models This book explores the application of the complex relationship between concept drift and cutting-edge large language models to address the problems and opportunities in navigating changing data landscapes. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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Paperback. Condizione: new. Paperback. This book explores the application of the complex relationship between concept drift and cutting-edge large language models to address the problems and opportunities in navigating changing data landscapes. It discusses the theoretical basis of concept drift and its consequences for large la…nguage models, particularly the transformative power of cutting-edge models such as GPT-3.5 and GPT-4. It offers real-world case studies to observe firsthand how concept drift influences the performance of language models in a variety of circumstances, delivering valuable lessons learnt and actionable takeaways. The book is designed for professionals, AI practitioners, and scholars, focused on natural language processing, machine learning, and artificial intelligence.Examines concept drift in AI, particularly its impact on large language modelsAnalyses how concept drift affects large language models and its theoretical and practical consequencesCovers detection methods and practical implementation challenges in language modelsShowcases examples of concept drift in GPT models and lessons learnt from their performanceIdentifies future research avenues and recommendations for practitioners tackling concept drift in large language models This book explores the application of the complex relationship between concept drift and cutting-edge large language models to address the problems and opportunities in navigating changing data landscapes. 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.
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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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EUR 88,70
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Paperback. Condizione: new. Paperback. This book explores the application of the complex relationship between concept drift and cutting-edge large language models to address the problems and opportunities in navigating changing data landscapes. It discusses the theoretical basis of concept drift and its consequences for large la…nguage models, particularly the transformative power of cutting-edge models such as GPT-3.5 and GPT-4. It offers real-world case studies to observe firsthand how concept drift influences the performance of language models in a variety of circumstances, delivering valuable lessons learnt and actionable takeaways. The book is designed for professionals, AI practitioners, and scholars, focused on natural language processing, machine learning, and artificial intelligence.Examines concept drift in AI, particularly its impact on large language modelsAnalyses how concept drift affects large language models and its theoretical and practical consequencesCovers detection methods and practical implementation challenges in language modelsShowcases examples of concept drift in GPT models and lessons learnt from their performanceIdentifies future research avenues and recommendations for practitioners tackling concept drift in large language models This book explores the application of the complex relationship between concept drift and cutting-edge large language models to address the problems and opportunities in navigating changing data landscapes. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
