Hands-On LLM: Building Applications, Implementation, and Techniques" is a comprehensive guide that equips readers with practical skills to harness the power of Large Language Models (LLMs). The book focuses on hands-on learning, providing step-by-step instructions and real-world examples to help readers understand and apply LLMs effectively.
Starting with an introduction to LLMs, the book covers their historical background, key concepts, and terminology. It explores various applications such as natural language processing, text generation, conversational AI, and more, highlighting their versatility in solving complex tasks.
The core of the book delves into building and training LLMs. Readers learn how to set up their development environment, select and preprocess data, and customize model architectures like GPT and BERT. Training strategies, hyperparameter tuning, and distributed training techniques are also covered in detail.
Practical projects form a significant part of the book, including text generation, sentiment analysis, named entity recognition (NER), question answering systems, and more. Each project guides readers through implementation, fine-tuning models for specific tasks, and integrating LLMs with other technologies such as knowledge graphs and computer vision.
Advanced topics like model optimization, deployment strategies, and transfer learning for adapting models to new domains are discussed extensively. The book emphasizes practicality by offering insights into deploying LLMs in production environments, scaling applications, and optimizing model performance through techniques like model compression and serving methodologies.
Case studies and industry-specific applications showcase success stories and lessons learned from implementing LLMs across healthcare, finance, retail, and beyond. The book concludes with an exploration of future trends in LLMs, discussing emerging research, technological advancements, and the ethical implications shaping the future of AI.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. Print on Demand. N° de réf. du vendeur I-9798332548642
Quantité disponible : Plus de 20 disponibles
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
PAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L0-9798332548642
Quantité disponible : Plus de 20 disponibles
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
Paperback. Etat : New. N° de réf. du vendeur LU-9798332548642
Quantité disponible : Plus de 20 disponibles
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L0-9798332548642
Quantité disponible : Plus de 20 disponibles
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In English. N° de réf. du vendeur ria9798332548642_new
Quantité disponible : Plus de 20 disponibles
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Paperback. Etat : new. Paperback. Hands-On LLM: Building Applications, Implementation, and Techniques" is a comprehensive guide that equips readers with practical skills to harness the power of Large Language Models (LLMs). The book focuses on hands-on learning, providing step-by-step instructions and real-world examples to help readers understand and apply LLMs effectively.Starting with an introduction to LLMs, the book covers their historical background, key concepts, and terminology. It explores various applications such as natural language processing, text generation, conversational AI, and more, highlighting their versatility in solving complex tasks.The core of the book delves into building and training LLMs. Readers learn how to set up their development environment, select and preprocess data, and customize model architectures like GPT and BERT. Training strategies, hyperparameter tuning, and distributed training techniques are also covered in detail.Practical projects form a significant part of the book, including text generation, sentiment analysis, named entity recognition (NER), question answering systems, and more. Each project guides readers through implementation, fine-tuning models for specific tasks, and integrating LLMs with other technologies such as knowledge graphs and computer vision.Advanced topics like model optimization, deployment strategies, and transfer learning for adapting models to new domains are discussed extensively. The book emphasizes practicality by offering insights into deploying LLMs in production environments, scaling applications, and optimizing model performance through techniques like model compression and serving methodologies.Case studies and industry-specific applications showcase success stories and lessons learned from implementing LLMs across healthcare, finance, retail, and beyond. The book concludes with an exploration of future trends in LLMs, discussing emerging research, technological advancements, and the ethical implications shaping the future of AI. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798332548642
Quantité disponible : 1 disponible(s)
Vendeur : Rarewaves.com UK, London, Royaume-Uni
Paperback. Etat : New. N° de réf. du vendeur LU-9798332548642
Quantité disponible : Plus de 20 disponibles