{"product_id":"9783032238290","title":"The Springer Series in Applied Machine Learning: Best Practices and Key Concepts","description":"\u003ch1\u003eThe Springer Series in Applied Machine Learning: Best Practices and Key Concepts\u003c\/h1\u003e \u003ch2\u003eStroud, David\u003c\/h2\u003e \u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan lang=\"EN-IN\"\u003eThis book presents a practitioner-oriented treatment of LLMOps: the engineering discipline required to deploy, scale, and govern large language model systems in production. \u003cem\u003eAdvanced Large Language Model Operations\u003c\/em\u003e explains why LLM deployments differ from classical MLOps — due to cost\/latency economics, non-deterministic behavior, retrieval and tool-calling pipelines, and new security and compliance threat models — and translates these realities into concrete operational patterns, metrics, and decision frameworks for real-world systems.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan lang=\"EN-IN\"\u003eThe text is organized into four parts spanning foundations, production delivery, optimization, and governance, culminating in a capstone implementation. It uses Ishtar AI\u003cstrong\u003e, \u003c\/strong\u003ea high-stakes, evidence-grounded journalism assistant, as a running case study to connect theory to practice across infrastructure and environment design, CI\/CD and continuous evaluation, observability, scaling, performance optimization, retrieval-augmented generation, multi-agent orchestration, robustness testing, and ethical\/responsible deployment.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"my-2 [\u0026amp;+p]:mt-4 [\u0026amp;_strong:has(+br)]:inline-block [\u0026amp;_strong:has(+br)]:pb-2\"\u003e\u003cem\u003eAdvanced Large Language Model Operations\u003c\/em\u003e offers an essential and in-depth roadmap for the deployment, management, and optimization of large language model (LLM) systems in enterprise and research settings. Bridging the persistent gap between model development and real-world application, this authoritative volume walks readers through the entire lifecycle of operationalizing LLMs, from foundational infrastructure and environment design to advanced strategies for monitoring, scaling, and optimization.  \u003c\/p\u003e\n\u003cp class=\"my-2 [\u0026amp;+p]:mt-4 [\u0026amp;_strong:has(+br)]:inline-block [\u0026amp;_strong:has(+br)]:pb-2\"\u003eEach chapter includes actionable checklists, advanced optimization techniques, and case-based insights that demonstrate both the successes and pitfalls of real-world LLM deployments. Readers with a strong grounding in machine learning and programming will gain the expertise to integrate LLMOps into their workflows, reduce deployment times, maximize scalability, and sustain high-performing language model solutions in production environments. \u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2026-08-29\u003c\/p\u003e \u003cp\u003eFormat: Hardcover\u003c\/p\u003e \u003cp\u003eISBN-13: 9783032238290\u003c\/p\u003e \u003cp\u003eDOI: \u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 584\u003c\/p\u003e ","brand":"Springer Nature Switzerland","offers":[{"title":"Default Title","offer_id":46612927414412,"sku":"9783032238290","price":49.49,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783032238290.jpg?v=1779943212","url":"https:\/\/lateknightbooks.com\/products\/9783032238290","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}