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Architecting Generative AI Applications. Build, deploy, and scale production-ready generative AI systems with LLMOps best practices Leonid Kuligin

(ebook) (audiobook) (audiobook) Język publikacji: angielski
Architecting Generative AI Applications. Build, deploy, and scale production-ready generative AI systems with LLMOps best practices Leonid Kuligin - okladka książki

Architecting Generative AI Applications. Build, deploy, and scale production-ready generative AI systems with LLMOps best practices Leonid Kuligin - okladka książki

Architecting Generative AI Applications. Build, deploy, and scale production-ready generative AI systems with LLMOps best practices Leonid Kuligin - audiobook MP3

Architecting Generative AI Applications. Build, deploy, and scale production-ready generative AI systems with LLMOps best practices Leonid Kuligin - audiobook CD

Autor:
Leonid Kuligin
Ocena:
Vibe-coding tools & coding assistants make it easy to spin up generative AI prototypes. Getting those prototypes into production is where most teams stall. This book is a practical guide to building production-ready generative AI applications that are reliable, scalable, and secure, and to understanding where traditional software best practices can clash with the realities of operating LLM-based systems.
Written by a Staff AI Engineer at Google, it takes you through the full AI product lifecycle: scoping and building effective prototypes, aligning them with business goals, and scaling enterprise-wide generative AI adoption. You will learn how to evaluate LLMs with offline metrics, human-in-the-loop methods, and statistical testing. Next, you will design core architectures such as RAG, vector databases, agents, and memory systems. Next, operationalize these systems with production-grade code, robust testing, DevOps, MLOps, and LLMOps workflows, including deployment and scaling on modern LLMOps platforms. The book also covers security, Responsible AI, and modern observability and reliability for generative AI systems. By the end you’ll learn how to run post-launch A/B tests, maintain systems over time, and measure business impact. The focus is on durable engineering principles, so your products succeed beyond the prototype stage.

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O autorze książki

Leonid Kuligin is an active contributor to LangChain and the author of the many Google Cloud integrations on LangChain. He has been building complex tech products for almost 20 years, developing intense data and Machine Learning applications. Leonid has a degree in Applied Mathematics and Physics, and a degree in Finance. Since 2023, he has been working with key Google Cloud customers on various generative AI initiatives.

Packt Publishing - inne książki

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