Machine Learning Writers (7 results)
- Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contact seller5-star sellerCondition: New
US$ 34.35
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Condition: New.
- Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contact seller5-star sellerCondition: Used - As new
US$ 39.19
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Condition: As New. Unread book in perfect condition.
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
Contact seller5-star sellerCondition: Used - As new
US$ 49.23
US$ 20.09 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Condition: As New. Unread book in perfect condition.
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
Contact seller5-star sellerCondition: New
US$ 49.64
US$ 20.09 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Condition: New.
- Softcover
- Print on Demand
Seller: California Books, Miami, FL, U.S.A.California Books
Contact seller4-star sellerCondition: New
US$ 37.00
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- Softcover
- Print on Demand
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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US$ 41.77
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Paperback. Condition: new. Paperback. Hands-On AI Engineering is a beginner, code-first guide to building production-grade LLM systemsWritten 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 PyTorchParameter-efficient fine-tuning using LoRA and QLoRA on consumer GPUsBuilding 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Softcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
Contact seller5-star sellerCondition: New
US$ 49.65
US$ 49.56 shippingShips from United Kingdom to U.S.A.Quantity: 1 available
Paperback. Condition: new. Paperback. Hands-On AI Engineering is a beginner, code-first guide to building production-grade LLM systemsWritten 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 PyTorchParameter-efficient fine-tuning using LoRA and QLoRA on consumer GPUsBuilding 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
