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物品 #:
228958251
AI Engineering: Building Applications with Foundation Models
89% of respondents would recommend this to a friend
物品 #:
228958251
HKD 467
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What Stands Out
Foundation Model Integration
Leverage advanced foundation models to streamline application development, ensuring high-performance and scalability while reducing time-to-market for innovative solutions.
Hands-On Practicality
Engaging, hands-on approach allows users to build real-world applications, enhancing learning outcomes and equipping engineers with applicable skills for immediate impact.
Comprehensive Guidance
In-depth coverage of AI engineering principles and practices provides clarity and direction, helping professionals navigate the complexities of AI-driven application development.
產品詳情
- 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 engineeringLearn the process for developing an AI application, the challenges at each step, and approaches to address themExplore various model adaptation techniques, including prompt engineering, RAG, fine-tuning, agents, and dataset engineering, and understand how and why they workExamine the bottlenecks for latency and cost when serving foundation models and learn how to overcome themChoose the right model, dataset, evaluation benchmarks, and metrics for your needsChip 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).
| Publisher | O'Reilly Media |
| Publication date | December 4, 2024 |
| Edition | 1st |
| Language | English |
| File size | 38.8 MB |
| Enhanced typesetting | Enabled |
| X-Ray | Not Enabled |
| Word Wise | Not Enabled |
| Print length | 875 pages |
| ISBN-13 | 978-1098166267 |
| Page Flip | Enabled |
| Item Weight | 0.5 lbs (230 grams) |
Who Should Buy?
-
Data Scientists
Ideal for data scientists looking to integrate advanced AI features into their applications using foundation models.
-
Software Developers
Great for software developers who want to enhance their programming skills with artificial intelligence capabilities.
-
AI Enthusiasts
Perfect for AI enthusiasts eager to learn about building applications that leverage the latest foundation models in AI.
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Beginners Without Background
Not suitable for absolute beginners in programming or AI who lack foundational knowledge.
產品敘述
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Machine Theory Editorial Review
**** The book *AI Engineering: Building Applications with Foundation Models* by Chip Huyen has garnered an overwhelmingly positive reception from customers, primarily for its clarity, depth, and accessibility. Reviewers highlight the expertly structured content, which begins with high-level AI concepts and gradually delves into more technical topics, catering to a broad audience, including both beginners and experienced developers. Readers appreciate that the book simplifies many complex aspects of AI, making them approachable and understandable. Customers who initially found the book's length daunting have expressed satisfaction, noting that it provides an equivalent educational experience to a graduate-level course. The author's background as an AI expert and educator at Stanford lends credence to the material, which is often praised for its thorough yet straightforward explanations free from excessive jargon. The audio version of the book has also received accolades for its accessibility, allowing readers to engage with the content during commutes, further enhancing its appeal. Notably, the book is seen as a valuable investment, illuminating the path for readers looking to deepen their understanding of AI and transition into AI engineering roles. Overall, *AI Engineering* is highly recommended as a foundational resource for both newcomers and those seeking to elevate their expertise in the evolving field of AI. **
Customer Reviews & Ratings
1023 客戶評分
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5 星
81%
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4 星
11%
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3 星
4%
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2 星
2%
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1 星
2%
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優點
- Clear and insightful explanations of complex AI concepts.
- Suitable for beginners and experienced developers alike.
- Well-structured starting with high-level concepts before moving to technical details.
- Accessible format, with positive feedback on the audiobook.
- Encourages deeper learning and provides a strong foundation for AI engineering.
- A valuable resource for those transitioning careers to AI.
缺點
- Some sections may not address every reader's specific needs.
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