Ultimate LLMOps for LLM Engineering by Kinjal Dand (.ePUB)+
File Size: 10 MB
Ultimate LLMOps for LLM Engineering: Engineering Reliable, Observable, and Scalable LLM Systems by Kinjal Dand
Requirements: .ePUB, .PDF reader, 10 MB
Overview: From Prototype to Production-Grade LLM Systems. Large Language Models (LLMs) are transforming how organizations build intelligent applications, yet taking them from experimentation to reliable production systems requires a new discipline—LLMOps. Ultimate LLMOps for LLM EngineeringU offers a comprehensive journey through the principles, tools, and workflows essential for operationalizing LLMs with confidence and efficiency. It begins by demystifying LLM fundamentals, model behavior, and the evolving landscape of MLOps, giving readers the context needed to design scalable AI systems. The core chapters dive into hands-on techniques that drive real-world LLM applications, including prompt management, LLM chaining, and Retrieval Augmented Generation (RAG). You will explore how to design LLM pipelines, build effective agentic systems, and orchestrate complex multi-step reasoning workflows. Each concept is supported with practical insights applicable across industries and platforms. This book is tailored for GenAI Developers, Machine Learning Engineers, and Data Scientists who want to build, deploy, and manage LLM-powered systems at scale. Readers should have foundational knowledge of AI/ML concepts, basic NLP familiarity, and experience with Python programming to fully benefit from the content.
Genre: Non-Fiction > Tech & Devices
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