Hands-On AI Engineering: Code First Guide to Building Production Grade LLM Systems with Python Accompanied with GitHub Tutorials Learn about Transformers Foundation Models & ML Pipelines
Hands-On AI Engineering: Code First Guide to Building Production Grade LLM Systems with Python Accompanied with GitHub Tutorials Learn about Transformers Foundation Models & ML Pipelines
Hands-On AI Engineering is a beginner, code-first guide to building production-grade LLM systems Written by 4 practicing AI engineers. It focuses on what AI teams deal with every day: performance limits, reliability, evaluation, and cost control. You'll learn how to design, build, and operate LLM systems that run efficiently, scale responsibly, and perform under pressure without relying on expensive cloud credits or black-box APIs. What's included: Training and fine-tuning neural networks with PyTorch Parameter ...
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Hands-On AI Engineering is a beginner, code-first guide to building production-grade LLM systems Written by 4 practicing AI engineers. It focuses on what AI teams deal with every day: performance limits, reliability, evaluation, and cost control. You'll learn how to design, build, and operate LLM systems that run efficiently, scale responsibly, and perform under pressure without relying on expensive cloud credits or black-box APIs. What's included: Training and fine-tuning neural networks with PyTorch Parameter-efficient fine-tuning using LoRA and QLoRA on consumer GPUs Building robust RAG pipelines (smart chunking, hybrid retrieval, ranking, and faithfulness checks) Proper evaluation methods (rubrics, LLM-as-a-judge, golden datasets, regression testing) Production realities: monitoring, guardrails, cost optimization, and reliable deployment Performance add-ons (last chapter) A companion GitHub repository, carefully sequenced projects you can follow along with and build yourself. Project 1 - Simple Companion Chat: Basic chatbot built around a single document. Project 2 - Personal Knowledge Q&A: Ask questions over your own files with grounded answers. Project 3 - Checked Q&A System: Compare AI answers against expected results. Project 4 - Conversational Agent: Multi-turn chat with memory and simple tools. Project 5 - Document Summarizer: Controlled summaries with basic quality checks. Project 6 - Chapter Explorer: Turn text into outlines and short quizzes. These projects mirror modern team workflows and give you something concrete to show in interviews or client work.
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Add this copy of Hands-On AI Engineering: Code First Guide to Building to cart. $37.18, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2026 by Independently Published.
Add this copy of Hands-On AI Engineering: Code First Guide to Building to cart. $45.99, like new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2026 by Independently Published.
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Fine. Trade paperback (US). Glued binding. 160 p. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Hands-On AI Engineering: Code First Guide to Building to cart. $46.38, new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2026 by Independently Published.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. Trade paperback (US). Glued binding. 160 p. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
