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AI Engineering : Building Applications with Foundation Models by Chip Huyen...
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Item specifics
- Condition
- ISBN
- 9781098166304
About this product
Product Identifiers
Publisher
O'reilly Media, Incorporated
ISBN-10
1098166302
ISBN-13
9781098166304
eBay Product ID (ePID)
21070936994
Product Key Features
Number of Pages
532 Pages
Language
English
Publication Name
Ai Engineering : Building Applications with Foundation Models
Subject
Enterprise Applications / Business Intelligence Tools, Machine Theory, Intelligence (Ai) & Semantics
Type
Textbook
Subject Area
Computers
Format
Trade Paperback
Dimensions
Item Height
1.1 in
Item Weight
32.3 Oz
Item Length
9.1 in
Item Width
7.1 in
Additional Product Features
Publication Year
2025
Synopsis
Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models. The book starts with an overview of AI engineering, explaining how it differs from traditional ML engineering and discussing the new AI stack. The more AI is used, the more opportunities there are for catastrophic failures, and therefore, the more important evaluation becomes. This book discusses different approaches to evaluating open-ended models, including the rapidly growing AI-as-a-judge approach. AI application developers will discover how to navigate the AI landscape, including models, datasets, evaluation benchmarks, and the seemingly infinite number of use cases and application patterns. You'll learn a framework for developing an AI application, starting with simple techniques and progressing toward more sophisticated methods, and discover how to efficiently deploy these applications. Understand what AI engineering is and how it differs from traditional machine learning engineering Learn the process for developing an AI application, the challenges at each step, and approaches to address them Explore various model adaptation techniques, including prompt engineering, RAG, fine-tuning, agents, and dataset engineering, and understand how and why they work Examine the bottlenecks for latency and cost when serving foundation models and learn how to overcome them Choose the right model, dataset, evaluation benchmarks, and metrics for your needs Chip Huyen works to accelerate data analytics on GPUs at Voltron Data. Previously, she was with Snorkel AI and NVIDIA, founded an AI infrastructure startup, and taught Machine Learning Systems Design at Stanford. She's the author of the book Designing Machine Learning Systems, an Amazon bestseller in AI. AI Engineering builds upon and is complementary to Designing Machine Learning Systems (O'Reilly)., Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models. The book starts with an overview of AI engineering, explaining how it differs from traditional ML engineering and discussing the new AI stack. The more AI is used, the more opportunities there are for catastrophic failures, and therefore, the more important evaluation becomes. This book discusses different approaches to evaluating open-ended models, including the rapidly growing AI-as-a-judge approach. AI application developers will discover how to navigate the AI landscape, including models, datasets, evaluation benchmarks, and the seemingly infinite number of use cases and application patterns. You'll learn a framework for developing an AI application, starting with simple techniques and progressing toward more sophisticated methods, and discover how to efficiently deploy these applications. Understand what AI engineering is and how it differs from traditional machine learning engineering Learn the process for developing an AI application, the challenges at each step, and approaches to address them Explore various model adaptation techniques, including prompt engineering, RAG, fine-tuning, agents, and dataset engineering, and understand how and why they work Examine the bottlenecks for latency and cost when serving foundation models and learn how to overcome them Choose the right model, dataset, evaluation benchmarks, and metrics for your needs Chip Huyen works to accelerate data analytics on GPUs at Voltron Data. Previously, she was with Snorkel AI and NVIDIA, founded an AI infrastructure startup, and taught Machine Learning Systems Design at Stanford. She's the author of the book Designing Machine Learning Systems, an Amazon bestseller in AI. AI Engineering builds upon and is complementary to Designing Machine Learning Systems (O'Reilly) .
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- b***h (1186)- Feedback left by buyer.Past 6 monthsVerified purchaseExcellent communication from the seller. The books were promptly shipped, so they happily arrived earlier than expected. They were very well packaged, which helped keep all of the books in perfect condition. The books are new, as described, and well priced. These were a gift, and the recipient is thrilled. I highly recommend this seller:)
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- b***h (1186)- Feedback left by buyer.Past 6 monthsVerified purchaseExcellent communication from the seller. The books were promptly shipped, so they happily arrived earlier than expected. They were very well packaged, which helped keep all of the books in perfect condition. The books are new, as described, and well priced. These were a gift, and the recipient is thrilled. I highly recommend this seller:)
- k***y (84)- Feedback left by buyer.Past monthVerified purchaseArrived quickly. Well wrapped and protected. Book in excellent condition as described and pictured. Easy transaction. Good communication. Good value. Great seller.
- k***n (222)- Feedback left by buyer.Past 6 monthsVerified purchaseI definitely recommend the seller, shipping was fast, excellent communication, product was exactly as described, the packaging was perfect for what I ordered. The quality of the product was great and excellent condition. Great value for my money. I definitely recommend buying.Lights Out : An into Darkness Novel by Navessa Allen (2024, Trade Paperback) (#335719616651)