Artikelnr.:
180595515
AI Engineering: Building Applications with Foundation Models
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Artikelnr.:
180595515
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Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications.
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Produktdetails
- 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). Daha fazla göster
| Yayınlanma Tarihi | 7 Ocak 2025 |
| Baskı | 1. |
| Dil | İngilizce |
| Baskı Uzunluğu | 528 sayfa |
| ISBN-10 | 1098166302 |
| ISBN-13 | 978-1098166304 |
| Boyutlar | 17.53 x 2.79 x 22.86 cm |
PRODUKTBESCHREIBUNG
AI Engineering: Building Applications with Foundation Models
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Kundenfragen und -antworten
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Frage:
Who is this book intended for?
Antworten: This book is for anyone interested in AI application development, regardless of their prior experience. -
Frage:
What will I learn from this book?
Antworten: You'll learn about AI engineering, model adaptation techniques, and practical steps to build and deploy AI applications. -
Frage:
Is prior knowledge of machine learning required?
Antworten: No, the book is designed for readers with minimal or no prior AI experience.
İngilizce Baskı Format: Kağıt Kapak Editorial Review
AI Engineering: Building Applications with Foundation Models is an essential read for anyone interested in the future of AI. Scheduled for publication on January 7, 2025, this comprehensive guide spans 528 pages and is presented in English. The book expertly covers fundamental concepts and practical applications, providing insightful perspectives essential for both budding and seasoned engineers. With a clear focus on modern methodologies, it encourages readers to explore and build with foundation models. This makes it a valuable resource in understanding the intricate dynamics of AI engineering.
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Vorteile
- Comprehensive coverage of AI engineering concepts
- Well-structured for both beginners and experts
- Practical applications enhance learning experience
- In-depth analysis of foundation models
- Upcoming publication keeps content relevant
Nachteile
- Exploration of some advanced topics could be challenging
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Merkmale und Vorteile
- Learn the essentials of AI engineering and its distinction from traditional ML engineering.
- Discover a framework for developing AI applications from simple to advanced techniques.
- Explore model adaptation techniques like prompt engineering and fine-tuning.
- Understand the bottlenecks related to latency and cost in serving foundation models.
- Choose the right models, datasets, and evaluation metrics tailored to your needs.
- Written by industry expert Chip Huyen, offering insights into practical AI application development.
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