خرید و دانلود نسخه کامل کتاب انگلیسی Hands-On LLM Serving and Optimization 2026

A comprehensive, engineering-focused guide to deploying and optimizing Large Language Models (LLMs) at scale. Emphasizing the “inference era,” the book tackles the cost and latency complexities of LLM hosting, providing practical, code-backed strategies for building robust, performant, and cost-efficient “AI token factories.”

Key topics include the foundations of model serving, balancing latency and throughput, and applying core optimization techniques such as batching, quantization, kernel fusion, continuous batching, prefix caching, and speculative decoding. It is designed for ML/AI engineers, backend developers, and system architects responsible for building or scaling inference infrastructures, RAG pipelines, and agentic platforms.