{"product_id":"building-robust-ai-evals-henry-v-primeaux-9798270714826","title":"Building Robust AI Evals: Proven Strategies for Testing, Monitoring, and Improving LLM Performance","description":"\u003cp\u003e\u003cb\u003eBuilding Robust AI Evals: Proven Strategies for Testing, Monitoring, and Improving LLM Performance\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eAre your AI models truly performing as intended, or are hidden failures silently undermining their reliability? In an era where large language models power critical business operations, customer interactions, and research breakthroughs, rigorous evaluation is not optional-it's essential. \u003cb\u003e\"Building Robust AI Evals\"\u003c\/b\u003e provides a comprehensive, hands-on blueprint for testing, monitoring, and improving LLM performance across real-world applications.\u003c\/p\u003e\u003cp\u003eThis book offers practical, actionable strategies for designing evaluation pipelines that are scalable, repeatable, and aligned with both business and technical goals. From defining meaningful metrics and curating high-quality datasets to implementing automated and human-in-the-loop evaluation workflows, you will learn how to ensure your AI systems are not only accurate but safe, reliable, and compliant.\u003c\/p\u003e\u003cp\u003eInside, you will discover how to: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\u003cp\u003eDesign effective evaluation frameworks that align with business objectives and technical requirements.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eImplement core and advanced metrics for LLMs, including semantic similarity, multi-step reasoning, and multi-modal assessment.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eBuild modular, automated evaluation pipelines with logging, monitoring, and regression testing for scalable deployments.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eDetect data drift, concept drift, and performance anomalies in production, and trigger timely retraining and re-evaluation.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eIntegrate safety, fairness, and compliance checks into all stages of evaluation, ensuring ethical and reliable model behavior.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eLeverage human-in-the-loop and multi-evaluator strategies to capture nuanced model performance beyond automated metrics.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eScale evaluation practices across teams and projects while maintaining governance, traceability, and knowledge transfer.\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eWhether you are an AI engineer, data scientist, or machine learning practitioner responsible for deploying large language models, this book equips you with the tools and frameworks to implement evaluation processes that are actionable, auditable, and robust. By following the techniques in this guide, you will reduce risk, improve model reliability, and gain confidence in the real-world performance of your AI systems.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Henry V. Primeaux\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9798270714826\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Independently Published\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 10\/20\/2025\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 232\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.90lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 10.00h x 7.00w x 0.49d","brand":"Henry V. Primeaux","offers":[{"title":"Paperback","offer_id":47761272471807,"sku":"9798270714826","price":20.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/files\/img_4ed1a059-a049-4473-bdfd-52c2685fd79d.jpg?v=1765514784","url":"https:\/\/www.whiterainbookhouse.com\/products\/building-robust-ai-evals-henry-v-primeaux-9798270714826","provider":"WR Book House","version":"1.0","type":"link"}