Bharath kumar bolla (7 resultados)
- Tapa blanda
Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 47,67
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
- Tapa blanda
Librería: Speedyhen, Hertfordshire, Reino UnidoSpeedyhen
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 53,93
Envío por EUR 47,92Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: NEW.
- Tapa blanda
Librería: moluna, Greven, Alemaniamoluna
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 76,99
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: New.
- Tapa blanda
- Impresión bajo demanda
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 47,66
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: 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 mast…ering 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.
- Tapa blanda
- Impresión bajo demanda
Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 50,23
Envío por EUR 8,00Se envía de Italia a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: new. Questo è un articolo print on demand.
- Tapa blanda
- Impresión bajo demanda
Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 61,38
Envío por EUR 43,24Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: 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 mast…ering 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.
- Tapa blanda
- Impresión bajo demanda
Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 101,68
Envío por EUR 31,71Se envía de Australia a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: 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 mast…ering 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.
