Makkaoui khalid (31 risultati)
Tiny Machine Learning Techniques for Constrained Devices
El-makkaoui, Khalid (EDT); Lamaakal, Ismail (EDT); Ouahbi, Ibrahim (EDT); Maleh, Yassine (EDT); El-latif, Ahmed A. Abd (EDT)
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 130,65
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Condizione: As New. Unread book in perfect condition.
Tiny Machine Learning Techniques for Constrained Devices
El-makkaoui, Khalid (EDT); Lamaakal, Ismail (EDT); Ouahbi, Ibrahim (EDT); Maleh, Yassine (EDT); El-latif, Ahmed A. Abd (EDT)
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 142,64
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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EUR 137,17
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Tiny Machine Learning Techniques for Constrained Devices
El-makkaoui, Khalid (EDT); Lamaakal, Ismail (EDT); Ouahbi, Ibrahim (EDT); Maleh, Yassine (EDT); El-latif, Ahmed A. Abd (EDT)
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 131,19
EUR 17,53 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 10 disponibili
Condizione: As New. Unread book in perfect condition.
Tiny Machine Learning Techniques for Constrained Devices
El-makkaoui, Khalid (EDT); Lamaakal, Ismail (EDT); Ouahbi, Ibrahim (EDT); Maleh, Yassine (EDT); El-latif, Ahmed A. Abd (EDT)
- Rilegato
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 131,68
EUR 17,53 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 10 disponibili
Condizione: New.
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
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EUR 131,70
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Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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EUR 152,43
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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: California Books, Miami, FL, U.S.A.California Books
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EUR 157,82
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Condizione: New.
Theory, Practice, and Future Direction of Large Language Models
Lamaakal, Ismail (EDT); Maleh, Yassine (EDT); El Makkaoui, Khalid (EDT); Ouahbi, Ibrahim (EDT); Abd El-latif, Ahmed (EDT)
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 178,67
EUR 2,26 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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EUR 182,33
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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EUR 177,36
EUR 5,87 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Theory, Practice, and Future Direction of Large Language Models
Lamaakal, Ismail (EDT); Maleh, Yassine (EDT); El Makkaoui, Khalid (EDT); Ouahbi, Ibrahim (EDT); Abd El-latif, Ahmed (EDT)
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 177,35
EUR 17,53 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
Theory, Practice, and Future Direction of Large Language Models
Lamaakal, Ismail (EDT); Maleh, Yassine (EDT); El Makkaoui, Khalid (EDT); Ouahbi, Ibrahim (EDT); Abd El-latif, Ahmed (EDT)
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 195,35
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Condizione: As New. Unread book in perfect condition.
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 194,21
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Hardcover. Condizione: Brand New. 248 pages. 9.18x6.12x9.45 inches. In Stock.
Theory, Practice, and Future Direction of Large Language Models
Lamaakal, Ismail (EDT); Maleh, Yassine (EDT); El Makkaoui, Khalid (EDT); Ouahbi, Ibrahim (EDT); Abd El-latif, Ahmed (EDT)
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 195,68
EUR 17,53 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Condizione: As New. Unread book in perfect condition.
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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EUR 222,11
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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EUR 215,60
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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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EUR 144,96
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Hardcover. Condizione: new. Hardcover. Tiny Machine Learning Techniques for Constrained Devices explores the cutting-edge field of Tiny Machine Learning (TinyML), enabling intelligent machine learning on highly resource-limited devices such as microcontrollers and edge Internet of Things (IoT) nodes. This book provides a compreh…ensive guide to designing, optimizing, securing, and applying TinyML models in real-world constrained environments.This book offers thorough coverage of key topics, including:Foundations and Optimization of TinyML: Covers microcontroller-centric power optimization, core principles, and algorithms essential for deploying efficient machine learning models on embedded systems with strict resource constraints.Applications of TinyML in Healthcare and IoT: Presents innovative use cases such as compact artificial intelligence (AI) solutions for healthcare challenges, real-time detection systems, and integration with low-power IoT and low-power wide-area network (LPWAN) technologies.Security and Privacy in TinyML: Addresses the unique challenges of securing TinyML deployments, including privacy-preserving techniques, blockchain integration for secure IoT applications, and methods for protecting resource-constrained devices.Emerging Trends and Future Directions: Explores the evolving landscape of TinyML research, highlighting new applications, adaptive frameworks, and promising avenues for future investigation.Practical Implementation and Case Studies: Offers hands-on insights and real-world examples demonstrating TinyML in action across diverse scenarios, providing guidance for engineers, researchers, and students.This book is an essential resource for embedded system designers, AI practitioners, cybersecurity professionals, and academics who want to harness the power of TinyML for smarter, more efficient, and secure edge intelligence solutions. Tiny Machine Learning Techniques for Constrained Devices explores the cutting-edge field of TinyML, enabling intelligent machine learning on highly resource-limited devices such as microcontrollers and edge IoT nodes. It is a guide to designing, optimizing, securing, and applying TinyML models in real-world constrained environments. 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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- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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EUR 153,68
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND.
Tiny Machine Learning Techniques for Constrained Devices
Khalid El-Makkaoui|Ismail Lamaakal|Ibrahim Ouahbi|Yassine Maleh|Ahmed A. Abd El-Latif
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- Print on Demand
Da: moluna, Greven, Germaniamoluna
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EUR 130,00
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Prof. Khalid El Makkaoui is an Associate Professor with the Department of Computer Science at the Multidisciplinary Faculty of Nador, University Mohammed Premier, Oujda, Morocco. His research interests focus on cyber…security and artificial intelli.
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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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EUR 160,69
EUR 43,24 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: new. Hardcover. Tiny Machine Learning Techniques for Constrained Devices explores the cutting-edge field of Tiny Machine Learning (TinyML), enabling intelligent machine learning on highly resource-limited devices such as microcontrollers and edge Internet of Things (IoT) nodes. This book provides a compreh…ensive guide to designing, optimizing, securing, and applying TinyML models in real-world constrained environments.This book offers thorough coverage of key topics, including:Foundations and Optimization of TinyML: Covers microcontroller-centric power optimization, core principles, and algorithms essential for deploying efficient machine learning models on embedded systems with strict resource constraints.Applications of TinyML in Healthcare and IoT: Presents innovative use cases such as compact artificial intelligence (AI) solutions for healthcare challenges, real-time detection systems, and integration with low-power IoT and low-power wide-area network (LPWAN) technologies.Security and Privacy in TinyML: Addresses the unique challenges of securing TinyML deployments, including privacy-preserving techniques, blockchain integration for secure IoT applications, and methods for protecting resource-constrained devices.Emerging Trends and Future Directions: Explores the evolving landscape of TinyML research, highlighting new applications, adaptive frameworks, and promising avenues for future investigation.Practical Implementation and Case Studies: Offers hands-on insights and real-world examples demonstrating TinyML in action across diverse scenarios, providing guidance for engineers, researchers, and students.This book is an essential resource for embedded system designers, AI practitioners, cybersecurity professionals, and academics who want to harness the power of TinyML for smarter, more efficient, and secure edge intelligence solutions. Tiny Machine Learning Techniques for Constrained Devices explores the cutting-edge field of TinyML, enabling intelligent machine learning on highly resource-limited devices such as microcontrollers and edge IoT nodes. It is a guide to designing, optimizing, securing, and applying TinyML models in real-world constrained environments. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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- Print on Demand
Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 183,46
EUR 31,67 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: new. Hardcover. Tiny Machine Learning Techniques for Constrained Devices explores the cutting-edge field of Tiny Machine Learning (TinyML), enabling intelligent machine learning on highly resource-limited devices such as microcontrollers and edge Internet of Things (IoT) nodes. This book provides a compreh…ensive guide to designing, optimizing, securing, and applying TinyML models in real-world constrained environments.This book offers thorough coverage of key topics, including:Foundations and Optimization of TinyML: Covers microcontroller-centric power optimization, core principles, and algorithms essential for deploying efficient machine learning models on embedded systems with strict resource constraints.Applications of TinyML in Healthcare and IoT: Presents innovative use cases such as compact artificial intelligence (AI) solutions for healthcare challenges, real-time detection systems, and integration with low-power IoT and low-power wide-area network (LPWAN) technologies.Security and Privacy in TinyML: Addresses the unique challenges of securing TinyML deployments, including privacy-preserving techniques, blockchain integration for secure IoT applications, and methods for protecting resource-constrained devices.Emerging Trends and Future Directions: Explores the evolving landscape of TinyML research, highlighting new applications, adaptive frameworks, and promising avenues for future investigation.Practical Implementation and Case Studies: Offers hands-on insights and real-world examples demonstrating TinyML in action across diverse scenarios, providing guidance for engineers, researchers, and students.This book is an essential resource for embedded system designers, AI practitioners, cybersecurity professionals, and academics who want to harness the power of TinyML for smarter, more efficient, and secure edge intelligence solutions. Tiny Machine Learning Techniques for Constrained Devices explores the cutting-edge field of TinyML, enabling intelligent machine learning on highly resource-limited devices such as microcontrollers and edge IoT nodes. It is a guide to designing, optimizing, securing, and applying TinyML models in real-world constrained environments. 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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- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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EUR 186,58
EUR 43,24 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Large Language Models (LLMs) represent a groundbreaking evolution in the field of artificial intelligence, blending theory, practice, and future potential to reshape industries and human-computer interaction. At the theoretical level, LLMs are rooted in deep learning architectures, which al…low them to process and generate natural language with fluency. In practice, they transform sectors like healthcare, education, customer service, and content creation, by automating tasks, providing insights, and enhancing user experiences. However, the use of LLMs also brings challenges, like ethical concerns regarding bias, misinformation, and data privacy, alongside technical issues like computational costs. The future of LLMs may focus on improving their efficiency, addressing ethical dilemmas, and integrating them into specialized applications. As research progresses, LLMs may become more adaptable, intelligent, and integrated into daily life, with the potential to redefine human-machine collaboration. Theory, Practice, and Future Direction of Large Language Models explores the transformative power of large language models (LLMs) by delving into their theoretical foundations, practical applications, and future potential. It showcases an array of applications across industries, demonstrating how LLMs solve real-world problems, enhance productivity, and drive innovation in fields like healthcare, finance, education, and entertainment. This book covers topics such as ethics and bias, robotics, and task automation, and is a useful resource for business owners, computer engineers, academicians, researchers, and data scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Da: preigu, Osnabrück, Germaniapreigu
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EUR 163,15
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Buch. Condizione: Neu. Tiny Machine Learning Techniques for Constrained Devices | Khalid El-Makkaoui (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2026 | Chapman and Hall/CRC | EAN 9781032897523 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu…Print on Demand.
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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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EUR 225,70
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Hardcover. Condizione: new. Hardcover. Large Language Models (LLMs) represent a groundbreaking evolution in the field of artificial intelligence, blending theory, practice, and future potential to reshape industries and human-computer interaction. At the theoretical level, LLMs are rooted in deep learning architectures, which al…low them to process and generate natural language with fluency. In practice, they transform sectors like healthcare, education, customer service, and content creation, by automating tasks, providing insights, and enhancing user experiences. However, the use of LLMs also brings challenges, like ethical concerns regarding bias, misinformation, and data privacy, alongside technical issues like computational costs. The future of LLMs may focus on improving their efficiency, addressing ethical dilemmas, and integrating them into specialized applications. As research progresses, LLMs may become more adaptable, intelligent, and integrated into daily life, with the potential to redefine human-machine collaboration. Theory, Practice, and Future Direction of Large Language Models explores the transformative power of large language models (LLMs) by delving into their theoretical foundations, practical applications, and future potential. It showcases an array of applications across industries, demonstrating how LLMs solve real-world problems, enhance productivity, and drive innovation in fields like healthcare, finance, education, and entertainment. This book covers topics such as ethics and bias, robotics, and task automation, and is a useful resource for business owners, computer engineers, academicians, researchers, and data scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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- Print on Demand
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 194,90
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Taschenbuch. Condizione: Neu. Theory, Practice, and Future Direction of Large Language Models | Ismail Lamaakal (u. a.) | Taschenbuch | Englisch | 2025 | IGI Global | EAN 9798369383889 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 232,96
EUR 62,94 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Large Language Models (LLMs) represent a groundbreaking evolution in the field of artificial intelligence, blending theory, practice, and future potential to reshape industries and human-computer interaction. At the theoretical level, L…LMs are rooted in deep learning architectures, which allow them to process and generate natural language with fluency. In practice, they transform sectors like healthcare, education, customer service, and content creation, by automating tasks, providing insights, and enhancing user experiences. However, the use of LLMs also brings challenges, like ethical concerns regarding bias, misinformation, and data privacy, alongside technical issues like computational costs. The future of LLMs may focus on improving their efficiency, addressing ethical dilemmas, and integrating them into specialized applications. As research progresses, LLMs may become more adaptable, intelligent, and integrated into daily life, with the potential to redefine human-machine collaboration. Theory, Practice, and Future Direction of Large Language Models explores the transformative power of large language models (LLMs) by delving into their theoretical foundations, practical applications, and future potential. It showcases an array of applications across industries, demonstrating how LLMs solve real-world problems, enhance productivity, and drive innovation in fields like healthcare, finance, education, and entertainment. This book covers topics such as ethics and bias, robotics, and task automation, and is a useful resource for business owners, computer engineers, academicians, researchers, and data scientists.
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- Print on Demand
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 236,25
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Buch. Condizione: Neu. Theory, Practice, and Future Direction of Large Language Models | Ismail Lamaakal (u. a.) | Buch | Englisch | 2025 | IGI Global | EAN 9798369383872 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
