Bharath kumar bolla (11 résultats)
- Couverture souple
Vendeur : California Books, Miami, FL, Etats-UnisCalifornia Books
Contacter le vendeurVendeur avec une évaluation de 4 étoilesEtat: Neuf
EUR 47,61
Frais de port gratuitsExpédition nationale : Etats-UnisQuantité disponible : Plus de 20 disponibles
Etat : New.
- Couverture souple
Vendeur : Rarewaves USA, HEBRON, KY, Etats-UnisRarewaves USA
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 49,38
Frais de port gratuitsExpédition nationale : Etats-UnisQuantité disponible : Plus de 20 disponibles
Paperback. Etat : New. The Large Language Model Recipes book is a comprehensive, practical guide designed to help developers, data scientists, and AI engineers navigate the rapidly evolving landscape of Large Language Models (LLMs). Moving beyond theory, this book provides a hands-on, recipe-based approach to mastering the entir…e LLMs lifecycle, from selecting the right open-source model to fine-tuning it on custom data and deploying it for production at scale.Starting with the fundamentals of setting up a robust development environment, the book guides you through the critical decisions of model selection (Llama, Mistral, Falcon) and data preparation. It offers deep dives into advanced training techniques, including full fine-tuning, instruction tuning, and parameter-efficient methods like LoRA and QLoRA that make training accessible on consumer hardware.The book doesn't stop at training. It tackles the crucial "last mile" of AI development: deployment and optimization. You will learn how to shrink models with quantization, serve them with high-throughput engines like vLLM and TGI, and evaluate their performance using industry-standard benchmarks. Finally, it explores cutting-edge frontiers, including Retrieval-Augmented Generation (RAG) for grounding models in real-time data, building multimodal vision-language applications, and designing autonomous AI agents.Whether you are building a specialized chatbot, a code assistant, or a complex reasoning agent, this book provides the tested recipes and code you need to develop efficient, scalable, and robust AI solutions today. What you will learn:Design production-ready LLM systems using the Feature/Training/Inference (FTI) framework Apply advanced fine-tuning methods, including LoRA and QLoRA, for efficient model adaptation Build and optimize RAG pipelines with effective retrieval strategies and vector databases Deploy optimized LLMs using quantization techniques and scalable inference frameworks Develop multimodal and agentic AI applications with vision-language models and autonomous agents Who this book is for:This book is ideal for software developers, machine learning engineers, data scientists, and technical researchers who want to move beyond using API endpoints and start.
- Couverture souple
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-UniRarewaves.com USA
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 76,93
Frais de port gratuitsExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Paperback. Etat : New. The Large Language Model Recipes book is a comprehensive, practical guide designed to help developers, data scientists, and AI engineers navigate the rapidly evolving landscape of Large Language Models (LLMs). Moving beyond theory, this book provides a hands-on, recipe-based approach to mastering the entir…e LLMs lifecycle, from selecting the right open-source model to fine-tuning it on custom data and deploying it for production at scale.Starting with the fundamentals of setting up a robust development environment, the book guides you through the critical decisions of model selection (Llama, Mistral, Falcon) and data preparation. It offers deep dives into advanced training techniques, including full fine-tuning, instruction tuning, and parameter-efficient methods like LoRA and QLoRA that make training accessible on consumer hardware.The book doesn't stop at training. It tackles the crucial "last mile" of AI development: deployment and optimization. You will learn how to shrink models with quantization, serve them with high-throughput engines like vLLM and TGI, and evaluate their performance using industry-standard benchmarks. Finally, it explores cutting-edge frontiers, including Retrieval-Augmented Generation (RAG) for grounding models in real-time data, building multimodal vision-language applications, and designing autonomous AI agents.Whether you are building a specialized chatbot, a code assistant, or a complex reasoning agent, this book provides the tested recipes and code you need to develop efficient, scalable, and robust AI solutions today. What you will learn:Design production-ready LLM systems using the Feature/Training/Inference (FTI) framework Apply advanced fine-tuning methods, including LoRA and QLoRA, for efficient model adaptation Build and optimize RAG pipelines with effective retrieval strategies and vector databases Deploy optimized LLMs using quantization techniques and scalable inference frameworks Develop multimodal and agentic AI applications with vision-language models and autonomous agents Who this book is for:This book is ideal for software developers, machine learning engineers, data scientists, and technical researchers who want to move beyond using API endpoints and start.
- Couverture souple
Vendeur : Rarewaves USA United, HEBRON, KY, Etats-UnisRarewaves USA United
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 52,31
EUR 42,80 expéditionExpédition nationale : Etats-UnisQuantité disponible : Plus de 20 disponibles
Paperback. Etat : New. The Large Language Model Recipes book is a comprehensive, practical guide designed to help developers, data scientists, and AI engineers navigate the rapidly evolving landscape of Large Language Models (LLMs). Moving beyond theory, this book provides a hands-on, recipe-based approach to mastering the entir…e LLMs lifecycle, from selecting the right open-source model to fine-tuning it on custom data and deploying it for production at scale.Starting with the fundamentals of setting up a robust development environment, the book guides you through the critical decisions of model selection (Llama, Mistral, Falcon) and data preparation. It offers deep dives into advanced training techniques, including full fine-tuning, instruction tuning, and parameter-efficient methods like LoRA and QLoRA that make training accessible on consumer hardware.The book doesn't stop at training. It tackles the crucial "last mile" of AI development: deployment and optimization. You will learn how to shrink models with quantization, serve them with high-throughput engines like vLLM and TGI, and evaluate their performance using industry-standard benchmarks. Finally, it explores cutting-edge frontiers, including Retrieval-Augmented Generation (RAG) for grounding models in real-time data, building multimodal vision-language applications, and designing autonomous AI agents.Whether you are building a specialized chatbot, a code assistant, or a complex reasoning agent, this book provides the tested recipes and code you need to develop efficient, scalable, and robust AI solutions today. What you will learn:Design production-ready LLM systems using the Feature/Training/Inference (FTI) framework Apply advanced fine-tuning methods, including LoRA and QLoRA, for efficient model adaptation Build and optimize RAG pipelines with effective retrieval strategies and vector databases Deploy optimized LLMs using quantization techniques and scalable inference frameworks Develop multimodal and agentic AI applications with vision-language models and autonomous agents Who this book is for:This book is ideal for software developers, machine learning engineers, data scientists, and technical researchers who want to move beyond using API endpoints and start.
- Couverture souple
Vendeur : Speedyhen, Hertfordshire, Royaume-UniSpeedyhen
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 53,93
EUR 47,92 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 1 disponible(s)
Etat : NEW.
- Couverture souple
Vendeur : moluna, Greven, Allemagnemoluna
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 76,99
EUR 48,99 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Etat : New.
- Couverture souple
Vendeur : Rarewaves.com UK, London, Royaume-UniRarewaves.com UK
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 72,42
EUR 75,97 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Paperback. Etat : New. The Large Language Model Recipes book is a comprehensive, practical guide designed to help developers, data scientists, and AI engineers navigate the rapidly evolving landscape of Large Language Models (LLMs). Moving beyond theory, this book provides a hands-on, recipe-based approach to mastering the entir…e LLMs lifecycle, from selecting the right open-source model to fine-tuning it on custom data and deploying it for production at scale.Starting with the fundamentals of setting up a robust development environment, the book guides you through the critical decisions of model selection (Llama, Mistral, Falcon) and data preparation. It offers deep dives into advanced training techniques, including full fine-tuning, instruction tuning, and parameter-efficient methods like LoRA and QLoRA that make training accessible on consumer hardware.The book doesn't stop at training. It tackles the crucial "last mile" of AI development: deployment and optimization. You will learn how to shrink models with quantization, serve them with high-throughput engines like vLLM and TGI, and evaluate their performance using industry-standard benchmarks. Finally, it explores cutting-edge frontiers, including Retrieval-Augmented Generation (RAG) for grounding models in real-time data, building multimodal vision-language applications, and designing autonomous AI agents.Whether you are building a specialized chatbot, a code assistant, or a complex reasoning agent, this book provides the tested recipes and code you need to develop efficient, scalable, and robust AI solutions today. What you will learn:Design production-ready LLM systems using the Feature/Training/Inference (FTI) framework Apply advanced fine-tuning methods, including LoRA and QLoRA, for efficient model adaptation Build and optimize RAG pipelines with effective retrieval strategies and vector databases Deploy optimized LLMs using quantization techniques and scalable inference frameworks Develop multimodal and agentic AI applications with vision-language models and autonomous agents Who this book is for:This book is ideal for software developers, machine learning engineers, data scientists, and technical researchers who want to move beyond using API endpoints and start.
- Couverture souple
- impression à la demande
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-UnisGrand Eagle Retail
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 47,60
Frais de port gratuitsExpédition nationale : Etats-UnisQuantité disponible : 1 disponible(s)
Paperback. Etat : new. Paperback. The Large Language Model Recipes book is a comprehensive, practical guide designed to help developers, data scientists, and AI engineers navigate the rapidly evolving landscape of Large Language Models (LLMs). Moving beyond theory, this book provides a hands-on, recipe-based approach to masterin…g the entire LLMs lifecycle, from selecting the right open-source model to fine-tuning it on custom data and deploying it for production at scale.Starting with the fundamentals of setting up a robust development environment, the book guides you through the critical decisions of model selection (Llama, Mistral, Falcon) and data preparation. It offers deep dives into advanced training techniques, including full fine-tuning, instruction tuning, and parameter-efficient methods like LoRA and QLoRA that make training accessible on consumer hardware.The book doesn't stop at training. It tackles the crucial "last mile" of AI development: deployment and optimization. You will learn how to shrink models with quantization, serve them with high-throughput engines like vLLM and TGI, and evaluate their performance using industry-standard benchmarks. Finally, it explores cutting-edge frontiers, including Retrieval-Augmented Generation (RAG) for grounding models in real-time data, building multimodal vision-language applications, and designing autonomous AI agents.Whether you are building a specialized chatbot, a code assistant, or a complex reasoning agent, this book provides the tested recipes and code you need to develop efficient, scalable, and robust AI solutions today. What you will learn:Design production-ready LLM systems using the Feature/Training/Inference (FTI) framework Apply advanced fine-tuning methods, including LoRA and QLoRA, for efficient model adaptation Build and optimize RAG pipelines with effective retrieval strategies and vector databases Deploy optimized LLMs using quantization techniques and scalable inference frameworks Develop multimodal and agentic AI applications with vision-language models and autonomous agents Who this book is for:This book is ideal for software developers, machine learning engineers, data scientists, and technical researchers who want to move beyond using API endpoints and start This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Couverture souple
- impression à la demande
Vendeur : Brook Bookstore On Demand, Napoli, NA, ItalieBrook Bookstore On Demand
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 50,23
EUR 8,00 expéditionExpédition depuis Italie vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Etat : new. Questo è un articolo print on demand.
- Couverture souple
- impression à la demande
Vendeur : CitiRetail, Stevenage, Royaume-UniCitiRetail
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 61,38
EUR 43,24 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 1 disponible(s)
Paperback. Etat : new. Paperback. The Large Language Model Recipes book is a comprehensive, practical guide designed to help developers, data scientists, and AI engineers navigate the rapidly evolving landscape of Large Language Models (LLMs). Moving beyond theory, this book provides a hands-on, recipe-based approach to masterin…g the entire LLMs lifecycle, from selecting the right open-source model to fine-tuning it on custom data and deploying it for production at scale.Starting with the fundamentals of setting up a robust development environment, the book guides you through the critical decisions of model selection (Llama, Mistral, Falcon) and data preparation. It offers deep dives into advanced training techniques, including full fine-tuning, instruction tuning, and parameter-efficient methods like LoRA and QLoRA that make training accessible on consumer hardware.The book doesn't stop at training. It tackles the crucial "last mile" of AI development: deployment and optimization. You will learn how to shrink models with quantization, serve them with high-throughput engines like vLLM and TGI, and evaluate their performance using industry-standard benchmarks. Finally, it explores cutting-edge frontiers, including Retrieval-Augmented Generation (RAG) for grounding models in real-time data, building multimodal vision-language applications, and designing autonomous AI agents.Whether you are building a specialized chatbot, a code assistant, or a complex reasoning agent, this book provides the tested recipes and code you need to develop efficient, scalable, and robust AI solutions today. What you will learn:Design production-ready LLM systems using the Feature/Training/Inference (FTI) framework Apply advanced fine-tuning methods, including LoRA and QLoRA, for efficient model adaptation Build and optimize RAG pipelines with effective retrieval strategies and vector databases Deploy optimized LLMs using quantization techniques and scalable inference frameworks Develop multimodal and agentic AI applications with vision-language models and autonomous agents Who this book is for:This book is ideal for software developers, machine learning engineers, data scientists, and technical researchers who want to move beyond using API endpoints and start This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
- Couverture souple
- impression à la demande
Vendeur : AussieBookSeller, Truganina, VIC, AustralieAussieBookSeller
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 101,81
EUR 31,67 expéditionExpédition depuis Australie vers Etats-UnisQuantité disponible : 1 disponible(s)
Paperback. Etat : new. Paperback. The Large Language Model Recipes book is a comprehensive, practical guide designed to help developers, data scientists, and AI engineers navigate the rapidly evolving landscape of Large Language Models (LLMs). Moving beyond theory, this book provides a hands-on, recipe-based approach to masterin…g the entire LLMs lifecycle, from selecting the right open-source model to fine-tuning it on custom data and deploying it for production at scale.Starting with the fundamentals of setting up a robust development environment, the book guides you through the critical decisions of model selection (Llama, Mistral, Falcon) and data preparation. It offers deep dives into advanced training techniques, including full fine-tuning, instruction tuning, and parameter-efficient methods like LoRA and QLoRA that make training accessible on consumer hardware.The book doesn't stop at training. It tackles the crucial "last mile" of AI development: deployment and optimization. You will learn how to shrink models with quantization, serve them with high-throughput engines like vLLM and TGI, and evaluate their performance using industry-standard benchmarks. Finally, it explores cutting-edge frontiers, including Retrieval-Augmented Generation (RAG) for grounding models in real-time data, building multimodal vision-language applications, and designing autonomous AI agents.Whether you are building a specialized chatbot, a code assistant, or a complex reasoning agent, this book provides the tested recipes and code you need to develop efficient, scalable, and robust AI solutions today. What you will learn:Design production-ready LLM systems using the Feature/Training/Inference (FTI) framework Apply advanced fine-tuning methods, including LoRA and QLoRA, for efficient model adaptation Build and optimize RAG pipelines with effective retrieval strategies and vector databases Deploy optimized LLMs using quantization techniques and scalable inference frameworks Develop multimodal and agentic AI applications with vision-language models and autonomous agents Who this book is for:This book is ideal for software developers, machine learning engineers, data scientists, and technical researchers who want to move beyond using API endpoints and start 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.
