AI Engineering: Building Applications with Foundation Models
BAM 207
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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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Detalji o proizvodu
| Date of publication | January 7, 2025 |
| Prints | 1. |
| Language | English |
| Print Length | 528 pages |
| ISBN-10 | 1098166302 |
| ISBN-13 | 978-1098166304 |
| Dimensions | 17.53 x 2.79 x 22.86 cm |
Who Should Buy?
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AI Enthusiasts
Individuals eager to understand foundational models and their applications in various AI projects and scenarios.
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Developers
Software engineers looking to integrate foundation models into their applications or seeking to enhance their AI skills.
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Researchers
Academics and professionals conducting research on AI advancement, focusing on foundational model development and innovations.
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Beginners
Those with minimal knowledge of AI might struggle to grasp the complex concepts introduced in this paper.
OPIS PROIZVODA
AI Engineering: Building Applications with Foundation Models
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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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Pros
- 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
Cons
- Exploration of some advanced topics could be challenging
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Karakteristike i prednosti
- 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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