{"product_id":"hands-on-ai-engineering-build-applications-with-python-transformers-prompt-foundation-models-llms-ml-pipelines-and-system-building-9798279292356","title":"Hands-On AI Engineering: Build Applications with Python, Transformers, Prompt, Foundation Models, LLMs, ML Pipelines, and System Building","description":"\u003cp\u003e • Author(s): Machine Learning Writers\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Logic Design\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eHands-On AI Engineering is a practical, code-first guide to building production-grade LLM systems, written by four practicing AI engineers. It focuses on what AI teams deal with every day: performance limits, reliability, evaluation, and cost control.\u003c\/p\u003e\u003cp\u003eYou'll learn how to design, build, and operate LLM systems that run efficiently, scale responsibly, and hold up under real users - without relying on expensive cloud credits or black-box APIs.\u003c\/p\u003e\u003ci\u003eWhat this book covers\u003c\/i\u003e\u003cul\u003e\n\u003cli\u003eTraining and fine-tuning neural networks with PyTorch\u003c\/li\u003e\n\u003cli\u003eFine-tuning transformers using LoRA and QLoRA on consumer hardware\u003c\/li\u003e\n\u003cli\u003eBuilding robust RAG pipelines: chunking strategies, hybrid retrieval, ranking, and faithfulness checks\u003c\/li\u003e\n\u003cli\u003eDeploying models with FastAPI\u003c\/li\u003e\n\u003cli\u003eEvaluating systems properly: rubrics, LLM-as-a-judge, golden datasets, regression testing, benchmarking\u003c\/li\u003e\n\u003cli\u003eMonitoring, failure handling, and cost-performance trade-offs\u003c\/li\u003e\n\u003cli\u003eDocumenting architectures and decisions so teams can trust and extend your work\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003c\/p\u003e\u003ci\u003ePerformance add-ons (last chapter)\u003c\/i\u003e\u003cp\u003eA free companion GitHub repository, carefully sequenced projects you can follow along with and build yourself.\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eProject 1 - Simple Companion Chat: \u003c\/b\u003eBasic chatbot built around a single document.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eProject 2 - Personal Knowledge Q\u0026amp;A: \u003c\/b\u003eAsk questions over your own files with grounded answers.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eProject 3 - Checked Q\u0026amp;A System: \u003c\/b\u003eCompare AI answers against expected results.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eProject 4 - Conversational Agent: \u003c\/b\u003eMulti-turn chat with memory and simple tools.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eProject 5 - Document Summarizer: \u003c\/b\u003eControlled summaries with basic quality checks.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eProject 6 - Chapter Explorer: \u003c\/b\u003e Turn text into outlines and short quizzes.\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eThis book gives you the engineering mindset needed to move from experiments to dependable systems.\u003c\/p\u003e\u003cp\u003eThe projects are designed to reflect real-world workflows which you can discuss confidently in interviews and use to stand out as an AI engineer. \u003c\/p\u003e\u003cp\u003e\u003ci\u003eUse wisely.\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47569246453911,"sku":"9798279292356","price":4802.0,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798279292356.webp?v=1774874154","url":"https:\/\/atlanticbooks.com\/products\/hands-on-ai-engineering-build-applications-with-python-transformers-prompt-foundation-models-llms-ml-pipelines-and-system-building-9798279292356","provider":"Atlantic Books","version":"1.0","type":"link"}